Chicago Bulls R Markdown
Leanne Szeto
5/8/2021
1. Introduction
In a basketball game, the objective of each team is to score more points than the other team to be the winner. As a team sport consisting of five players, each team player requires default skill set of their specific roles.
Load required packages
library(ggplot2)
library(tidyverse)
library(car)
library(broom)2. Reading and cleaning the raw data
To begin with, the team winning percentage will first be considered. With the five data sets provided, the two 2018-2019 NBA team statistics files are first be read and combined to one data set. All variables from these two files are included at this first stage. No missing values are shown. Instead of using the Wins(W) and Loses(L) data values, Winning Percentage (win_per) is calculated by (Wins / Total Games*100%) to get a continuous factor valuables for further expression. The remaining two data sets of player statistics and player salaries, as well as the expected player contracts budge, will be considered at the later stage.
Data source
df <- read.csv("~/Desktop/Reproducible Projects/Data/Raw/2018-19_nba_team-statistics_1.csv")
df2 <- read.csv("~/Desktop/Reproducible Projects/Data/Raw/2018-19_nba_team-statistics_2.csv")
data_both <- left_join(df,df2, by = "Team")str(data_both)## 'data.frame': 30 obs. of 49 variables:
## $ Rk.x : int 1 2 3 4 5 6 7 8 9 10 ...
## $ Team : chr "Milwaukee Bucks" "Golden State Warriors" "Toronto Raptors" "Utah Jazz" ...
## $ Age : num 26.9 28.4 27.3 27.3 29.2 26.2 24.9 25.7 25.7 27 ...
## $ W : int 60 57 58 50 53 53 54 49 49 48 ...
## $ L : int 22 25 24 32 29 29 28 33 33 34 ...
## $ PW : int 61 56 56 54 53 51 51 52 50 50 ...
## $ PL : int 21 26 26 28 29 31 31 30 32 32 ...
## $ MOV : num 8.87 6.46 6.09 5.26 4.77 4.2 3.95 4.44 3.4 3.33 ...
## $ SOS : num -0.82 -0.04 -0.6 0.03 0.19 0.24 0.24 -0.54 0.15 -0.57 ...
## $ SRS : num 8.04 6.42 5.49 5.28 4.96 4.43 4.19 3.9 3.56 2.76 ...
## $ ORtg : num 114 116 113 111 116 ...
## $ DRtg : num 105 110 107 106 111 ...
## $ NRtg : num 8.6 6.4 6 5.2 4.8 4.2 4.1 4.4 3.3 3.4 ...
## $ Pace : num 103.3 100.9 100.2 100.3 97.9 ...
## $ FTr : num 0.255 0.227 0.247 0.295 0.279 0.258 0.232 0.215 0.266 0.242 ...
## $ X3PAr : num 0.419 0.384 0.379 0.394 0.519 0.339 0.348 0.381 0.347 0.292 ...
## $ TS. : num 0.583 0.596 0.579 0.572 0.581 0.568 0.558 0.567 0.545 0.561 ...
## $ eFG. : num 0.55 0.565 0.543 0.538 0.542 0.528 0.527 0.534 0.514 0.53 ...
## $ TOV. : num 12 12.6 12.4 13.4 12 12.1 11.9 11.5 11.7 12.4 ...
## $ ORB. : num 20.8 22.5 21.9 22.9 22.8 26.6 26.6 21.6 26 21.9 ...
## $ FT.FGA: num 0.197 0.182 0.198 0.217 0.221 0.21 0.175 0.173 0.19 0.182 ...
## $ DRB. : num 80.3 77.1 77.1 80.3 74.4 77.9 78 77 78.2 76.2 ...
## $ X : logi NA NA NA NA NA NA ...
## $ X.1 : logi NA NA NA NA NA NA ...
## $ X.2 : logi NA NA NA NA NA NA ...
## $ Rk.y : int 1 2 8 17 11 6 20 14 7 22 ...
## $ G : int 82 82 82 82 82 82 82 82 82 82 ...
## $ MP : int 19780 19805 19880 19755 19830 19855 19730 19780 19855 19705 ...
## $ FG : int 3555 3612 3460 3314 3218 3470 3439 3451 3497 3390 ...
## $ FGA : int 7471 7361 7305 7082 7163 7427 7384 7423 7706 7135 ...
## $ FG. : num 0.476 0.491 0.474 0.468 0.449 0.467 0.466 0.465 0.454 0.475 ...
## $ X3P : int 1105 1087 1015 993 1323 904 903 1032 932 779 ...
## $ X3PA : int 3134 2824 2771 2789 3721 2520 2571 2829 2677 2081 ...
## $ X3P. : num 0.353 0.385 0.366 0.356 0.356 0.359 0.351 0.365 0.348 0.374 ...
## $ X2P : int 2450 2525 2445 2321 1895 2566 2536 2419 2565 2611 ...
## $ X2PA : int 4337 4537 4534 4293 3442 4907 4813 4594 5029 5054 ...
## $ X2P. : num 0.565 0.557 0.539 0.541 0.551 0.523 0.527 0.527 0.51 0.517 ...
## $ FT : int 1471 1339 1449 1540 1582 1558 1294 1282 1461 1298 ...
## $ FTA : int 1904 1672 1803 2092 2001 1914 1714 1598 2049 1727 ...
## $ FT. : num 0.773 0.801 0.804 0.736 0.791 0.814 0.755 0.802 0.713 0.752 ...
## $ ORB : int 762 797 786 820 836 967 972 804 1031 762 ...
## $ DRB : int 3316 2990 2920 2981 2613 2968 2832 2849 2911 2766 ...
## $ TRB : int 4078 3787 3706 3801 3449 3935 3804 3653 3942 3528 ...
## $ AST : int 2136 2413 2085 2133 1741 1887 2245 2155 1917 2128 ...
## $ STL : int 615 625 680 663 700 546 634 706 766 713 ...
## $ BLK : int 486 525 437 483 405 413 363 435 425 404 ...
## $ TOV : int 1137 1169 1150 1240 1094 1135 1102 1052 1145 1122 ...
## $ PF : int 1608 1757 1724 1728 1803 1669 1644 1670 1839 1594 ...
## $ PTS : int 9686 9650 9384 9161 9341 9402 9075 9216 9387 8857 ...head(data_both)## Rk.x Team Age W L PW PL MOV SOS SRS ORtg DRtg NRtg
## 1 1 Milwaukee Bucks 26.9 60 22 61 21 8.87 -0.82 8.04 113.8 105.2 8.6
## 2 2 Golden State Warriors 28.4 57 25 56 26 6.46 -0.04 6.42 115.9 109.5 6.4
## 3 3 Toronto Raptors 27.3 58 24 56 26 6.09 -0.60 5.49 113.1 107.1 6.0
## 4 4 Utah Jazz 27.3 50 32 54 28 5.26 0.03 5.28 110.9 105.7 5.2
## 5 5 Houston Rockets 29.2 53 29 53 29 4.77 0.19 4.96 115.5 110.7 4.8
## 6 6 Portland Trail Blazers 26.2 53 29 51 31 4.20 0.24 4.43 114.7 110.5 4.2
## Pace FTr X3PAr TS. eFG. TOV. ORB. FT.FGA DRB. X X.1 X.2 Rk.y G MP
## 1 103.3 0.255 0.419 0.583 0.550 12.0 20.8 0.197 80.3 NA NA NA 1 82 19780
## 2 100.9 0.227 0.384 0.596 0.565 12.6 22.5 0.182 77.1 NA NA NA 2 82 19805
## 3 100.2 0.247 0.379 0.579 0.543 12.4 21.9 0.198 77.1 NA NA NA 8 82 19880
## 4 100.3 0.295 0.394 0.572 0.538 13.4 22.9 0.217 80.3 NA NA NA 17 82 19755
## 5 97.9 0.279 0.519 0.581 0.542 12.0 22.8 0.221 74.4 NA NA NA 11 82 19830
## 6 99.1 0.258 0.339 0.568 0.528 12.1 26.6 0.210 77.9 NA NA NA 6 82 19855
## FG FGA FG. X3P X3PA X3P. X2P X2PA X2P. FT FTA FT. ORB DRB TRB
## 1 3555 7471 0.476 1105 3134 0.353 2450 4337 0.565 1471 1904 0.773 762 3316 4078
## 2 3612 7361 0.491 1087 2824 0.385 2525 4537 0.557 1339 1672 0.801 797 2990 3787
## 3 3460 7305 0.474 1015 2771 0.366 2445 4534 0.539 1449 1803 0.804 786 2920 3706
## 4 3314 7082 0.468 993 2789 0.356 2321 4293 0.541 1540 2092 0.736 820 2981 3801
## 5 3218 7163 0.449 1323 3721 0.356 1895 3442 0.551 1582 2001 0.791 836 2613 3449
## 6 3470 7427 0.467 904 2520 0.359 2566 4907 0.523 1558 1914 0.814 967 2968 3935
## AST STL BLK TOV PF PTS
## 1 2136 615 486 1137 1608 9686
## 2 2413 625 525 1169 1757 9650
## 3 2085 680 437 1150 1724 9384
## 4 2133 663 483 1240 1728 9161
## 5 1741 700 405 1094 1803 9341
## 6 1887 546 413 1135 1669 9402tail(data_both)## Rk.x Team Age W L PW PL MOV SOS SRS ORtg DRtg NRtg
## 25 25 Washington Wizards 26.5 32 50 34 48 -2.90 -0.40 -3.30 111.1 113.9 -2.8
## 26 26 Atlanta Hawks 25.1 29 53 27 55 -6.02 -0.04 -6.06 108.1 113.9 -5.8
## 27 27 Chicago Bulls 24.0 22 60 21 61 -8.41 0.10 -8.32 104.8 113.2 -8.4
## 28 28 Phoenix Suns 24.0 19 63 19 63 -9.34 0.73 -8.61 105.9 115.1 -9.2
## 29 29 New York Knicks 23.4 17 65 19 63 -9.21 0.28 -8.93 104.5 113.7 -9.2
## 30 30 Cleveland Cavaliers 25.2 19 63 19 63 -9.61 0.22 -9.39 107.7 117.6 -9.9
## Pace FTr X3PAr TS. eFG. TOV. ORB. FT.FGA DRB. X X.1 X.2 Rk.y G MP
## 25 101.4 0.266 0.370 0.567 0.531 12.3 21.3 0.204 74.1 NA NA NA 10 82 19930
## 26 103.9 0.255 0.403 0.555 0.522 14.3 24.7 0.192 76.4 NA NA NA 12 82 19855
## 27 99.0 0.235 0.295 0.541 0.505 12.7 19.4 0.184 77.3 NA NA NA 27 82 19905
## 28 100.5 0.259 0.335 0.552 0.514 13.8 20.5 0.202 72.5 NA NA NA 23 82 19880
## 29 99.6 0.270 0.334 0.529 0.490 12.4 22.1 0.205 76.1 NA NA NA 28 82 19780
## 30 96.6 0.236 0.332 0.540 0.503 12.2 23.7 0.187 77.0 NA NA NA 29 82 19755
## FG FGA FG. X3P X3PA X3P. X2P X2PA X2P. FT FTA FT. ORB DRB
## 25 3456 7387 0.468 930 2731 0.341 2526 4656 0.543 1508 1963 0.768 794 2679
## 26 3392 7524 0.451 1067 3034 0.352 2325 4490 0.518 1443 1918 0.752 955 2825
## 27 3266 7205 0.453 745 2123 0.351 2521 5082 0.496 1328 1695 0.783 718 2799
## 28 3289 7164 0.459 790 2400 0.329 2499 4764 0.525 1447 1858 0.779 748 2563
## 29 3134 7241 0.433 823 2421 0.340 2311 4820 0.479 1484 1956 0.759 857 2811
## 30 3189 7184 0.444 847 2388 0.355 2342 4796 0.488 1342 1694 0.792 879 2619
## TRB AST STL BLK TOV PF PTS
## 25 3473 2154 683 379 1154 1701 9350
## 26 3780 2118 675 419 1397 1932 9294
## 27 3517 1796 603 351 1159 1663 8605
## 28 3311 1957 735 418 1279 1932 8815
## 29 3668 1646 557 422 1151 1713 8575
## 30 3498 1698 534 195 1106 1642 8567## check duplicated values
duplicated(data_both)## [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [25] FALSE FALSE FALSE FALSE FALSE FALSE## Handling Missing values
complete(data_both)## Rk.x Team Age W L PW PL MOV SOS SRS ORtg DRtg
## 1 1 Milwaukee Bucks 26.9 60 22 61 21 8.87 -0.82 8.04 113.8 105.2
## 2 2 Golden State Warriors 28.4 57 25 56 26 6.46 -0.04 6.42 115.9 109.5
## 3 3 Toronto Raptors 27.3 58 24 56 26 6.09 -0.60 5.49 113.1 107.1
## 4 4 Utah Jazz 27.3 50 32 54 28 5.26 0.03 5.28 110.9 105.7
## 5 5 Houston Rockets 29.2 53 29 53 29 4.77 0.19 4.96 115.5 110.7
## 6 6 Portland Trail Blazers 26.2 53 29 51 31 4.20 0.24 4.43 114.7 110.5
## 7 7 Denver Nuggets 24.9 54 28 51 31 3.95 0.24 4.19 113.0 108.9
## 8 8 Boston Celtics 25.7 49 33 52 30 4.44 -0.54 3.90 112.2 107.8
## 9 9 Oklahoma City Thunder 25.7 49 33 50 32 3.40 0.15 3.56 110.3 107.0
## 10 10 Indiana Pacers 27.0 48 34 50 32 3.33 -0.57 2.76 109.9 106.5
## 11 11 Philadelphia 76ers 26.4 51 31 48 34 2.70 -0.44 2.25 112.6 110.0
## 12 12 San Antonio Spurs 28.8 48 34 45 37 1.68 0.12 1.80 112.9 111.2
## 13 13 Los Angeles Clippers 27.2 48 34 43 39 0.85 0.23 1.09 112.4 111.5
## 14 14 Orlando Magic 25.7 42 40 43 39 0.71 -0.43 0.28 108.9 108.1
## 15 15 Brooklyn Nets 25.4 42 40 41 41 -0.07 -0.33 -0.40 109.6 109.7
## 16 16 Miami Heat 27.0 39 43 40 42 -0.23 -0.22 -0.45 107.3 107.6
## 17 17 Detroit Pistons 26.9 41 41 40 42 -0.24 -0.31 -0.56 109.0 109.2
## 18 18 Sacramento Kings 24.8 39 43 38 44 -1.12 0.31 -0.81 110.4 111.5
## 19 19 Dallas Mavericks 26.9 33 49 38 44 -1.28 0.42 -0.87 109.4 110.7
## 20 20 Minnesota Timberwolves 26.2 36 46 37 45 -1.50 0.48 -1.02 111.4 112.9
## 21 21 New Orleans Pelicans 25.7 33 49 38 44 -1.33 0.23 -1.10 111.4 112.6
## 22 22 Charlotte Hornets 26.6 39 43 38 44 -1.10 -0.22 -1.32 111.4 112.5
## 23 23 Los Angeles Lakers 26.2 37 45 37 45 -1.72 0.39 -1.33 107.8 109.5
## 24 24 Memphis Grizzlies 27.7 33 49 34 48 -2.60 0.51 -2.08 106.1 108.8
## 25 25 Washington Wizards 26.5 32 50 34 48 -2.90 -0.40 -3.30 111.1 113.9
## 26 26 Atlanta Hawks 25.1 29 53 27 55 -6.02 -0.04 -6.06 108.1 113.9
## 27 27 Chicago Bulls 24.0 22 60 21 61 -8.41 0.10 -8.32 104.8 113.2
## 28 28 Phoenix Suns 24.0 19 63 19 63 -9.34 0.73 -8.61 105.9 115.1
## 29 29 New York Knicks 23.4 17 65 19 63 -9.21 0.28 -8.93 104.5 113.7
## 30 30 Cleveland Cavaliers 25.2 19 63 19 63 -9.61 0.22 -9.39 107.7 117.6
## NRtg Pace FTr X3PAr TS. eFG. TOV. ORB. FT.FGA DRB. X X.1 X.2 Rk.y G
## 1 8.6 103.3 0.255 0.419 0.583 0.550 12.0 20.8 0.197 80.3 NA NA NA 1 82
## 2 6.4 100.9 0.227 0.384 0.596 0.565 12.6 22.5 0.182 77.1 NA NA NA 2 82
## 3 6.0 100.2 0.247 0.379 0.579 0.543 12.4 21.9 0.198 77.1 NA NA NA 8 82
## 4 5.2 100.3 0.295 0.394 0.572 0.538 13.4 22.9 0.217 80.3 NA NA NA 17 82
## 5 4.8 97.9 0.279 0.519 0.581 0.542 12.0 22.8 0.221 74.4 NA NA NA 11 82
## 6 4.2 99.1 0.258 0.339 0.568 0.528 12.1 26.6 0.210 77.9 NA NA NA 6 82
## 7 4.1 97.7 0.232 0.348 0.558 0.527 11.9 26.6 0.175 78.0 NA NA NA 20 82
## 8 4.4 99.6 0.215 0.381 0.567 0.534 11.5 21.6 0.173 77.0 NA NA NA 14 82
## 9 3.3 102.8 0.266 0.347 0.545 0.514 11.7 26.0 0.190 78.2 NA NA NA 7 82
## 10 3.4 98.1 0.242 0.292 0.561 0.530 12.4 21.9 0.182 76.2 NA NA NA 22 82
## 11 2.6 101.6 0.312 0.342 0.574 0.532 12.9 24.5 0.241 78.6 NA NA NA 4 82
## 12 1.7 98.3 0.237 0.286 0.572 0.534 11.0 21.0 0.194 79.4 NA NA NA 18 82
## 13 0.9 101.7 0.326 0.295 0.575 0.529 12.7 22.0 0.258 76.0 NA NA NA 5 82
## 14 0.8 98.1 0.216 0.360 0.550 0.518 11.9 22.0 0.168 79.7 NA NA NA 24 82
## 15 -0.1 100.8 0.284 0.403 0.556 0.520 13.0 23.8 0.211 76.4 NA NA NA 15 82
## 16 -0.3 98.2 0.247 0.368 0.542 0.515 13.1 24.8 0.172 77.6 NA NA NA 26 82
## 17 -0.2 97.4 0.262 0.394 0.544 0.509 12.3 24.8 0.195 78.7 NA NA NA 25 82
## 18 -1.1 103.1 0.244 0.321 0.554 0.524 11.5 23.1 0.177 75.5 NA NA NA 9 82
## 19 -1.3 99.0 0.291 0.422 0.555 0.519 12.7 22.7 0.216 77.5 NA NA NA 21 82
## 20 -1.5 100.2 0.267 0.315 0.552 0.511 11.4 24.6 0.210 74.9 NA NA NA 13 82
## 21 -1.2 103.3 0.254 0.324 0.563 0.529 12.6 24.1 0.193 76.8 NA NA NA 3 82
## 22 -1.1 98.7 0.257 0.378 0.554 0.514 10.9 21.7 0.205 77.1 NA NA NA 19 82
## 23 -1.7 103.2 0.257 0.342 0.554 0.527 13.4 22.2 0.180 76.4 NA NA NA 16 82
## 24 -2.7 96.6 0.272 0.342 0.548 0.508 12.9 20.0 0.210 77.6 NA NA NA 30 82
## 25 -2.8 101.4 0.266 0.370 0.567 0.531 12.3 21.3 0.204 74.1 NA NA NA 10 82
## 26 -5.8 103.9 0.255 0.403 0.555 0.522 14.3 24.7 0.192 76.4 NA NA NA 12 82
## 27 -8.4 99.0 0.235 0.295 0.541 0.505 12.7 19.4 0.184 77.3 NA NA NA 27 82
## 28 -9.2 100.5 0.259 0.335 0.552 0.514 13.8 20.5 0.202 72.5 NA NA NA 23 82
## 29 -9.2 99.6 0.270 0.334 0.529 0.490 12.4 22.1 0.205 76.1 NA NA NA 28 82
## 30 -9.9 96.6 0.236 0.332 0.540 0.503 12.2 23.7 0.187 77.0 NA NA NA 29 82
## MP FG FGA FG. X3P X3PA X3P. X2P X2PA X2P. FT FTA FT. ORB
## 1 19780 3555 7471 0.476 1105 3134 0.353 2450 4337 0.565 1471 1904 0.773 762
## 2 19805 3612 7361 0.491 1087 2824 0.385 2525 4537 0.557 1339 1672 0.801 797
## 3 19880 3460 7305 0.474 1015 2771 0.366 2445 4534 0.539 1449 1803 0.804 786
## 4 19755 3314 7082 0.468 993 2789 0.356 2321 4293 0.541 1540 2092 0.736 820
## 5 19830 3218 7163 0.449 1323 3721 0.356 1895 3442 0.551 1582 2001 0.791 836
## 6 19855 3470 7427 0.467 904 2520 0.359 2566 4907 0.523 1558 1914 0.814 967
## 7 19730 3439 7384 0.466 903 2571 0.351 2536 4813 0.527 1294 1714 0.755 972
## 8 19780 3451 7423 0.465 1032 2829 0.365 2419 4594 0.527 1282 1598 0.802 804
## 9 19855 3497 7706 0.454 932 2677 0.348 2565 5029 0.510 1461 2049 0.713 1031
## 10 19705 3390 7135 0.475 779 2081 0.374 2611 5054 0.517 1298 1727 0.752 762
## 11 19805 3407 7233 0.471 889 2474 0.359 2518 4759 0.529 1742 2258 0.771 892
## 12 19805 3468 7248 0.478 812 2071 0.392 2656 5177 0.513 1408 1720 0.819 757
## 13 19830 3384 7178 0.471 821 2118 0.388 2563 5060 0.507 1853 2340 0.792 796
## 14 19780 3316 7307 0.454 937 2633 0.356 2379 4674 0.509 1231 1575 0.782 822
## 15 19980 3301 7358 0.449 1047 2965 0.353 2254 4393 0.513 1555 2088 0.745 900
## 16 19730 3251 7218 0.450 928 2658 0.349 2323 4560 0.509 1238 1782 0.695 921
## 17 19855 3185 7238 0.440 993 2854 0.348 2192 4384 0.500 1415 1893 0.747 936
## 18 19730 3541 7637 0.464 927 2455 0.378 2614 5182 0.504 1354 1865 0.726 906
## 19 19780 3182 7122 0.447 1022 3002 0.340 2160 4120 0.524 1541 2076 0.742 832
## 20 19830 3413 7483 0.456 827 2357 0.351 2586 5126 0.504 1570 1995 0.787 923
## 21 19755 3581 7563 0.473 842 2449 0.344 2739 5114 0.536 1462 1921 0.761 909
## 22 19830 3297 7362 0.448 977 2783 0.351 2320 4579 0.507 1510 1895 0.797 814
## 23 19780 3491 7425 0.470 847 2541 0.333 2644 4884 0.541 1336 1910 0.699 835
## 24 19880 3113 6924 0.450 811 2368 0.342 2302 4556 0.505 1453 1882 0.772 723
## 25 19930 3456 7387 0.468 930 2731 0.341 2526 4656 0.543 1508 1963 0.768 794
## 26 19855 3392 7524 0.451 1067 3034 0.352 2325 4490 0.518 1443 1918 0.752 955
## 27 19905 3266 7205 0.453 745 2123 0.351 2521 5082 0.496 1328 1695 0.783 718
## 28 19880 3289 7164 0.459 790 2400 0.329 2499 4764 0.525 1447 1858 0.779 748
## 29 19780 3134 7241 0.433 823 2421 0.340 2311 4820 0.479 1484 1956 0.759 857
## 30 19755 3189 7184 0.444 847 2388 0.355 2342 4796 0.488 1342 1694 0.792 879
## DRB TRB AST STL BLK TOV PF PTS
## 1 3316 4078 2136 615 486 1137 1608 9686
## 2 2990 3787 2413 625 525 1169 1757 9650
## 3 2920 3706 2085 680 437 1150 1724 9384
## 4 2981 3801 2133 663 483 1240 1728 9161
## 5 2613 3449 1741 700 405 1094 1803 9341
## 6 2968 3935 1887 546 413 1135 1669 9402
## 7 2832 3804 2245 634 363 1102 1644 9075
## 8 2849 3653 2155 706 435 1052 1670 9216
## 9 2911 3942 1917 766 425 1145 1839 9387
## 10 2766 3528 2128 713 404 1122 1594 8857
## 11 3025 3917 2207 606 432 1223 1745 9445
## 12 2910 3667 2013 501 386 992 1487 9156
## 13 2936 3732 1970 561 385 1193 1913 9442
## 14 2902 3724 2095 543 445 1082 1526 8800
## 15 2919 3819 1954 539 339 1236 1763 9204
## 16 2879 3800 1991 627 448 1208 1712 8668
## 17 2752 3688 1845 569 331 1135 1811 8778
## 18 2819 3725 2083 679 363 1095 1751 9363
## 19 2884 3716 1918 533 351 1167 1650 8927
## 20 2750 3673 2018 683 411 1074 1664 9223
## 21 2969 3878 2216 610 441 1215 1732 9466
## 22 2778 3592 1905 591 405 1001 1550 9081
## 23 2985 3820 2096 618 440 1284 1701 9165
## 24 2703 3426 1963 684 448 1147 1801 8490
## 25 2679 3473 2154 683 379 1154 1701 9350
## 26 2825 3780 2118 675 419 1397 1932 9294
## 27 2799 3517 1796 603 351 1159 1663 8605
## 28 2563 3311 1957 735 418 1279 1932 8815
## 29 2811 3668 1646 557 422 1151 1713 8575
## 30 2619 3498 1698 534 195 1106 1642 8567sum(is.na(data_both))## [1] 90which(is.na(data_both), arr.ind = TRUE)## row col
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## [90,] 30 25naniar::vis_miss(data_both)
data_both[is.na(data_both)] = 0sum(is.na(data_both))## [1] 0# calculating wining percentage(continuous variables)
data_both <- mutate(data_both, win_per = W/G * 100)
data_both$win_per <- round(data_both$win_per, 2)3. Exploratory analysis
To create visualisation to determine how each individual explanatory variable (ORtg, DRtg, MP, FG, etc.) relates to the winning percentage (win_per), total 34 plots are formed by plotting winning percentage against each variables form the combined data set.
## Relationship between offensive rating and win%
ggplot(data = data_both, aes(x = ORtg, y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = ORtg, y = win_per))## [1] 0.8410927## Relationship between defensive rating and win%
ggplot(data = data_both, aes(x = DRtg, y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = DRtg, y = win_per))## [1] -0.7598063## Relationship between Net rating and win%
ggplot(data = data_both, aes(x = NRtg, y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = NRtg, y = win_per))## [1] 0.9800259## Relationship between Pace and win%
ggplot(data = data_both, aes(x = Pace, y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = Pace, y = win_per))## [1] 0.08896707## Relationship between free throw attempt rate and win%
ggplot(data = data_both, aes(x = FTr, y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = FTr, y = win_per))## [1] 0.02348235## Relationship between 3-points attempt rate and win%
ggplot(data = data_both, aes(x = X3PAr, y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = X3PAr, y = win_per))## [1] 0.2842707## Relationship between true shooting% and win%
## Points/[2*(Field Goals Attempted + 0.44 * Free Throws Attempted)]
ggplot(data = data_both, aes(x = TS. , y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = TS. , y = win_per))## [1] 0.7570871## Relationship between effective field goal% and win%
## ((FGM + 0.5 * 3PM)) / FGA
ggplot(data = data_both, aes(x = eFG. , y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = eFG. , y = win_per))## [1] 0.7818481## Relationship between turnover% and win%
ggplot(data = data_both, aes(x = TOV. , y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = TOV. , y = win_per))## [1] -0.3068452## Relationship between offensive rebound% and win%
ggplot(data = data_both, aes(x = ORB. , y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = ORB. , y = win_per))## [1] 0.2354179##Relationship between free throws per field goal attempt and win%
ggplot(data = data_both, aes(x = FT.FGA , y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = FT.FGA , y = win_per))## [1] 0.0861065## Relationship between defensive rebound% and win%
ggplot(data = data_both, aes(x = DRB. , y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = DRB. , y = win_per))## [1] 0.4483858## Relationship between minutes played and win%
ggplot(data = data_both, aes(x = MP, y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = MP, y = win_per))## [1] -0.144398## Relationship between field goal and win%
ggplot(data = data_both, aes(x = FG, y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = FG, y = win_per))## [1] 0.5259582## Relationship between field goal attempt and win%
ggplot(data = data_both, aes(x = FGA, y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = FGA, y = win_per))## [1] 0.1679701## Relationship between field goal% and win%
data_both$FG. <- data_both$FG. * 100
ggplot(data = data_both, aes(x = FG., y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = FG., y = win_per))## [1] 0.6108395## Relationship between 3-points field goal and win%
ggplot(data = data_both, aes(x = X3P, y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = X3P, y = win_per))## [1] 0.4838393## Relationship between 3-points field goal attemp and win%
ggplot(data = data_both, aes(x = X3PA, y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = X3PA, y = win_per))## [1] 0.312573## Relationship between 3-points field goal% and win%
data_both$X3P. <- data_both$X3P. * 100
ggplot(data = data_both, aes(x = X3P., y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = X3P., y = win_per))## [1] 0.5419247## Relationship between 2-points field goal and win%
ggplot(data = data_both, aes(x = X2P, y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = X2P, y = win_per))## [1] 0.06873326## Relationship between 2-points field goal attempt and win%
ggplot(data = data_both, aes(x = X2PA, y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = X2PA, y = win_per))## [1] -0.2181137## Relationship between 2-points fiels goals% and win%
data_both$X2P. <- data_both$X2P. * 100
ggplot(data = data_both, aes(x = X2P., y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = X2P., y = win_per))## [1] 0.6008858## Relationship between free throw and win%
ggplot(data = data_both, aes(x = FT, y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = FT, y = win_per))## [1] 0.1297826## ## Relationship between free throw attempt and win%
ggplot(data = data_both, aes(x = FTA, y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = FTA, y = win_per))## [1] 0.06231113## ## Relationship between free throw% and win%
data_both$FT. <- data_both$FT. * 100
ggplot(data = data_both, aes(x = FT. , y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = FT. , y = win_per))## [1] 0.1611426##Relationship between offensive rebounds and win%
ggplot(data = data_both, aes(x = ORB, y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = ORB, y = win_per))## [1] 0.07860252## Relationship between defensive rebounds and win%
ggplot(data = data_both, aes(x = DRB, y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = DRB, y = win_per))## [1] 0.5749105## Relationship between total rebounds and win%
ggplot(data = data_both, aes(x = TRB, y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = TRB, y = win_per))## [1] 0.52877## Relationship between assist and win%
ggplot(data = data_both, aes(x = AST, y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = AST, y = win_per))## [1] 0.5018845## Relationship between steal and win%
ggplot(data = data_both, aes(x = STL, y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = STL, y = win_per))## [1] 0.1020406## Relationship between block and win%
ggplot(data = data_both, aes(x = BLK, y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = BLK, y = win_per))## [1] 0.4448873## Relationship between turnover and win%
ggplot(data = data_both, aes(x = TOV, y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = TOV, y = win_per))## [1] -0.2470975## Relationship between personal foul and win%
ggplot(data = data_both, aes(x = PF, y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = PF, y = win_per))## [1] -0.1606102## Relationship between points and win%
ggplot(data = data_both, aes(x = PTS, y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = PTS, y = win_per))## [1] 0.6605931## Relationship between age and win%
ggplot(data = data_both, aes(x = Age, y = win_per)) +
geom_point(colour = "black") +
geom_smooth(method = "lm")## `geom_smooth()` using formula 'y ~ x'
with(data_both, cor(x = Age, y = win_per))## [1] 0.6217657Multiple Linear Regression
By investigating on the above plots, 4 variables with high strength of the winning percentage relationship as well as P-value, are considered for further data modelling.
1) TS. (true shoot percentage)
2) TOV (turn over)
3) TRB (total rebound)
4) Age
##TS. + TOV + TRB + Age
fit <- lm(win_per ~ TS. + TOV + TRB + Age , data = data_both)
tidy(fit, conf.int = TRUE)## # A tibble: 5 x 7
## term estimate std.error statistic p.value conf.low conf.high
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 (Intercept) -366. 53.5 -6.84 0.000000359 -476. -256.
## 2 TS. 472. 121. 3.92 0.000615 224. 721.
## 3 TOV -0.0439 0.0164 -2.68 0.0129 -0.0777 -0.0101
## 4 TRB 0.0374 0.00798 4.68 0.0000849 0.0209 0.0538
## 5 Age 2.44 1.33 1.84 0.0781 -0.295 5.17summary(fit)##
## Call:
## lm(formula = win_per ~ TS. + TOV + TRB + Age, data = data_both)
##
## Residuals:
## Min 1Q Median 3Q Max
## -13.8481 -4.6074 0.2328 3.9613 13.8741
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -365.99543 53.49450 -6.842 3.59e-07 ***
## TS. 472.31489 120.61488 3.916 0.000615 ***
## TOV -0.04394 0.01641 -2.677 0.012933 *
## TRB 0.03736 0.00798 4.682 8.49e-05 ***
## Age 2.43787 1.32708 1.837 0.078125 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6.991 on 25 degrees of freedom
## Multiple R-squared: 0.8042, Adjusted R-squared: 0.7729
## F-statistic: 25.67 on 4 and 25 DF, p-value: 1.552e-084. Data modelling and results
A multiple linear regression is then conducted to model win_per based on the four selected variables (TS., TOV, TRB, Age) to get the correlation coefficient value for the preliminary model formula.
Independence
By using durbinWatson Test, the D-W statistic is 1.44 which is under value of 2.0. Thus, the model is assumed to be independence of observations.
car::durbinWatsonTest(fit)## lag Autocorrelation D-W Statistic p-value
## 1 0.3968211 1.119269 0.006
## Alternative hypothesis: rho != 0Outliers
All plots are within the range of -3 to +3. Therefore, it is considered to be no outliner.
std_res <- rstandard(fit)
points <- 1:length(std_res)
ggplot(data = NULL, aes(x = points, y = std_res))+
geom_point() +
ylim(c(-4,4)) +
geom_hline(yintercept = c (-3,3), colour = "blue", linetype = "dashed")
Leverage Points
There are no hat values greater than 1, it is considered that there are no high leverage points that may have potential to influence the model.
hats <- hatvalues(fit)
ggplot(data = NULL, aes(x = points, y = hats)) +
geom_point()
hat_labels <- if_else(hats >= 0.4, paste(points), "")
ggplot(data = NULL, aes(x = points, y = hats)) +
geom_point() +
geom_text(aes(label = hat_labels), nudge_y = 0.02)
Influential points
Two plot are found (10 and 18) bit far away from the other points, which may have high influence, these two points would be filtered out when creating the new model. Removing these points has improved the R-squared value from 0.82 to 0.8682.
cook <- cooks.distance(fit)
ggplot(data = NULL, aes(x = points, y = cook)) +
geom_point()
cook_labels <- if_else(cook >= 0.1, paste(points), "")
ggplot(data = NULL, aes( x = points, y = cook)) +
geom_point() +
geom_text(aes(label = cook_labels), nudge_y = 0.02)
## Remove Potentially High Influence Points
outliers <-c(7,12)
filtered_df <- data_both %>%
filter(!Rk.x %in% outliers)fit2 <- lm(win_per ~ TS. + TOV + TRB + Age , data = filtered_df)
tidy(fit2, conf.int = TRUE)## # A tibble: 5 x 7
## term estimate std.error statistic p.value conf.low conf.high
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 (Intercept) -369. 47.7 -7.74 0.0000000748 -468. -270.
## 2 TS. 427. 109. 3.93 0.000667 202. 652.
## 3 TOV -0.0436 0.0157 -2.78 0.0106 -0.0759 -0.0112
## 4 TRB 0.0357 0.00715 4.99 0.0000479 0.0209 0.0505
## 5 Age 3.73 1.26 2.95 0.00711 1.12 6.35summary(fit2)##
## Call:
## lm(formula = win_per ~ TS. + TOV + TRB + Age, data = filtered_df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -12.5413 -3.9485 0.6496 3.8068 10.2021
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -3.690e+02 4.766e+01 -7.743 7.48e-08 ***
## TS. 4.269e+02 1.086e+02 3.931 0.000667 ***
## TOV -4.355e-02 1.566e-02 -2.781 0.010613 *
## TRB 3.569e-02 7.155e-03 4.989 4.79e-05 ***
## Age 3.733e+00 1.263e+00 2.955 0.007108 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6.226 on 23 degrees of freedom
## Multiple R-squared: 0.8488, Adjusted R-squared: 0.8225
## F-statistic: 32.28 on 4 and 23 DF, p-value: 3.953e-09Homoscedasticity
The plot does not show evidence of heteroscedasticity. It is considered to be Homoscedasiticity.
res <- residuals(fit2)
fitted <- predict(fit2)
ggplot( data = NULL, aes(x = fitted, y = res))+
geom_point(colour = "dodgerblue")+
geom_hline(yintercept = 0, colour = "red", linetype = "dashed")
#Normality ## The conducted histogram looks normal, which supports model normality.
ggplot(data = NULL, aes(x = res)) +
geom_histogram(colour = "black", fill = "pink", binwidth = 4)
ggplot(data = NULL, aes(sample = res)) +
stat_qq() + stat_qq_line()
#Multicollinearity ## All vif values are < 4, which supports the model to have no multicollinearity influencing the standard errors of the coefficients.
car::vif(fit2)## TS. TOV TRB Age
## 1.952931 1.100724 1.137471 1.888074##Linearity
car::avPlots(fit2)
Compare
filtered_df <- mutate(filtered_df, exp_win = -369 + TS. * 426.9 + TOV * -0.04355 + TRB * 0.03569 + Age * 3.73282)
ggplot(data = filtered_df, aes(x = win_per, y = exp_win)) +
geom_point()+
geom_abline()
with(filtered_df, cor(x = win_per, y = exp_win))## [1] 0.9213Players
## combining player data and salaries
p <- read.csv("~/Desktop/Reproducible Projects/Data/Raw/2018-19_nba_player-statistics.csv")
ps <- read.csv("~/Desktop/Reproducible Projects/Data/Raw/2018-19_nba_player-salaries.csv")
pms <- left_join(p,ps, by = "player_name")Handling missing data
complete(pms)## player_name Pos Age Tm G GS MP FG FGA FG. X3P X3PA
## 1 Alex Abrines SG 25 OKC 31 2 588 56 157 0.357 41 127
## 2 Quincy Acy PF 28 PHO 10 0 123 4 18 0.222 2 15
## 3 Jaylen Adams PG 22 ATL 34 1 428 38 110 0.345 25 74
## 4 Steven Adams C 25 OKC 80 80 2669 481 809 0.595 0 2
## 5 Bam Adebayo C 21 MIA 82 28 1913 280 486 0.576 3 15
## 6 Deng Adel SF 21 CLE 19 3 194 11 36 0.306 6 23
## 7 DeVaughn Akoon-Purcell SG 25 DEN 7 0 22 3 10 0.300 0 4
## 8 LaMarcus Aldridge C 33 SAS 81 81 2687 684 1319 0.519 10 42
## 9 Rawle Alkins SG 21 CHI 10 1 120 13 39 0.333 3 12
## 10 Grayson Allen SG 23 UTA 38 2 416 67 178 0.376 32 99
## 11 Jarrett Allen C 20 BRK 80 80 2096 335 568 0.590 6 45
## 12 Kadeem Allen SG 26 NYK 19 1 416 65 141 0.461 17 36
## 13 Al-Farouq Aminu PF 28 POR 81 81 2292 257 593 0.433 96 280
## 14 Justin Anderson SF 25 ATL 48 4 463 64 157 0.408 24 77
## 15 Kyle Anderson SF 25 MEM 43 40 1281 150 276 0.543 9 34
## 16 Ryan Anderson PF 30 MIA 10 0 44 2 9 0.222 2 6
## 17 Ryan Anderson PF 30 PHO 15 8 278 19 60 0.317 7 34
## 18 Ryan Anderson PF 30 TOT 25 8 322 21 69 0.304 9 40
## 19 Ike Anigbogu C 20 IND 3 0 6 0 3 0.000 0 0
## 20 Giannis Antetokounmpo PF 24 MIL 72 72 2358 721 1247 0.578 52 203
## 21 Kostas Antetokounmpo PF 21 DAL 2 0 11 0 3 0.000 0 0
## 22 Carmelo Anthony PF 34 HOU 10 2 294 49 121 0.405 21 64
## 23 OG Anunoby SF 21 TOR 67 6 1352 183 404 0.453 67 202
## 24 Ryan Arcidiacono PG 24 CHI 81 32 1961 187 418 0.447 81 217
## 25 Trevor Ariza SF 33 PHO 26 26 884 86 227 0.379 50 139
## 26 Trevor Ariza SF 33 WAS 43 43 1465 208 509 0.409 95 295
## 27 Trevor Ariza SF 33 TOT 69 69 2349 294 736 0.399 145 434
## 28 DJ Augustin PG 31 ORL 81 81 2269 318 677 0.470 131 311
## 29 Deandre Ayton C 20 PHO 71 70 2183 509 870 0.585 0 4
## 30 Dwayne Bacon SG 23 CHO 43 13 759 122 257 0.475 38 87
## 31 Marvin Bagley PF 19 SAC 62 4 1567 356 706 0.504 30 96
## 32 Ron Baker SG 25 WAS 4 0 45 0 4 0.000 0 4
## 33 Ron Baker SG 25 TOT 15 0 152 4 20 0.200 1 13
## 34 Ron Baker SG 25 NYK 11 0 107 4 16 0.250 1 9
## 35 Wade Baldwin PG 22 POR 16 0 94 10 33 0.303 2 9
## 36 Lonzo Ball PG 21 LAL 47 45 1423 185 456 0.406 75 228
## 37 Mo Bamba C 20 ORL 47 1 766 117 243 0.481 21 70
## 38 JJ Barea PG 34 DAL 38 0 752 161 385 0.418 38 128
## 39 Harrison Barnes SF 26 SAC 28 28 949 141 310 0.455 53 130
## 40 Harrison Barnes PF 26 DAL 49 49 1584 290 717 0.404 121 311
## 41 Harrison Barnes PF-SF 26 TOT 77 77 2533 431 1027 0.420 174 441
## 42 Will Barton SG 28 DEN 43 38 1189 185 460 0.402 67 196
## 43 Keita Bates-Diop SF 23 MIN 30 3 503 60 142 0.423 13 52
## 44 Nicolas Batum SF 30 CHO 75 72 2354 253 562 0.450 116 298
## 45 Jerryd Bayless PG 30 MIN 34 6 657 82 230 0.357 29 98
## 46 Aron Baynes C 32 BOS 51 18 821 105 223 0.471 21 61
## 47 Kent Bazemore SG 29 ATL 67 35 1643 278 691 0.402 96 300
## 48 Bradley Beal SG 25 WAS 82 82 3028 764 1609 0.475 209 596
## 49 Malik Beasley SG 22 DEN 81 18 1879 349 737 0.474 163 405
## 50 Michael Beasley PF 30 LAL 26 2 277 75 153 0.490 3 17
## 51 Marco Belinelli SG 32 SAS 79 1 1815 285 690 0.413 147 395
## 52 Jordan Bell C 24 GSW 68 3 788 99 192 0.516 0 2
## 53 DeAndre' Bembry SG 24 ATL 82 15 1931 275 616 0.446 50 173
## 54 Dragan Bender PF 21 PHO 46 27 826 88 197 0.447 22 101
## 55 Dairis Bertans SG 29 NOP 12 0 167 12 47 0.255 10 34
## 56 Davis Bertans PF 26 SAS 76 12 1632 204 453 0.450 145 338
## 57 Patrick Beverley PG 30 LAC 78 49 2137 194 477 0.407 112 282
## 58 Khem Birch C 26 ORL 50 1 643 91 151 0.603 0 1
## 59 Bismack Biyombo C 26 CHO 54 32 783 89 156 0.571 0 0
## 60 Nemanja Bjelica PF 30 SAC 77 70 1788 284 593 0.479 103 257
## 61 Antonio Blakeney SG 22 CHI 57 3 829 166 396 0.419 36 91
## 62 Eric Bledsoe PG 29 MIL 78 78 2272 470 971 0.484 124 377
## 63 Jaron Blossomgame SF 25 CLE 27 4 439 47 106 0.443 10 39
## 64 Bogdan Bogdanovic SG 26 SAC 70 17 1947 361 863 0.418 134 372
## 65 Bojan Bogdanovic SF 29 IND 81 81 2573 522 1051 0.497 164 386
## 66 Andrew Bogut C 34 GSW 11 5 134 18 36 0.500 0 0
## 67 Jonah Bolden PF 23 PHI 44 10 639 80 162 0.494 34 96
## 68 Isaac Bonga PG 19 LAL 22 0 120 5 33 0.152 0 8
## 69 Devin Booker SG 22 PHO 64 64 2242 586 1255 0.467 135 414
## 70 Chris Boucher PF 26 TOR 28 0 163 34 76 0.447 12 37
## 71 Avery Bradley SG 28 MEM 14 14 442 87 188 0.463 28 73
## 72 Avery Bradley SG 28 LAC 49 49 1463 161 420 0.383 58 172
## 73 Avery Bradley SG 28 TOT 63 63 1905 248 608 0.408 86 245
## 74 Tony Bradley C 21 UTA 3 0 36 8 16 0.500 0 0
## 75 Corey Brewer SF 32 PHI 7 3 140 20 49 0.408 4 14
## 76 Corey Brewer SF 32 SAC 24 0 352 33 74 0.446 10 30
## 77 Corey Brewer SF 32 TOT 31 3 492 53 123 0.431 14 44
## 78 Mikal Bridges SF 22 PHO 82 56 2417 242 563 0.430 105 313
## 79 Miles Bridges SF 20 CHO 80 25 1696 237 511 0.464 65 200
## 80 Isaiah Briscoe PG 22 ORL 39 0 559 55 138 0.399 11 34
## 81 Ryan Broekhoff SG 28 DAL 42 0 453 57 126 0.452 38 93
## 82 Malcolm Brogdon SG 26 MIL 64 64 1832 378 748 0.505 104 244
## 83 Dillon Brooks SF 23 MEM 18 0 330 49 122 0.402 15 40
## 84 MarShon Brooks SG 30 MEM 29 0 387 76 169 0.450 15 54
## 85 Bruce Brown SG 22 DET 74 56 1449 125 314 0.398 24 93
## 86 Jaylen Brown SG 22 BOS 74 25 1913 368 792 0.465 95 276
## 87 Lorenzo Brown PG 28 TOR 26 0 212 23 71 0.324 6 28
## 88 Sterling Brown SG 23 MIL 58 7 1034 145 312 0.465 53 147
## 89 Troy Brown SF 19 WAS 52 10 730 97 234 0.415 22 69
## 90 Jalen Brunson PG 22 DAL 73 38 1591 264 565 0.467 63 181
## 91 Thomas Bryant C 21 WAS 72 53 1496 309 502 0.616 33 99
## 92 Reggie Bullock SG 27 LAL 19 16 524 63 153 0.412 34 99
## 93 Reggie Bullock SG 27 DET 44 44 1355 182 441 0.413 114 294
## 94 Reggie Bullock SG 27 TOT 63 60 1879 245 594 0.412 148 393
## 95 Trey Burke PG 26 DAL 25 1 436 88 190 0.463 26 73
## 96 Trey Burke PG 26 NYK 33 7 689 148 358 0.413 30 86
## 97 Trey Burke PG 26 TOT 58 8 1125 236 548 0.431 56 159
## 98 Alec Burks SG 27 SAC 13 0 127 9 20 0.450 0 6
## 99 Alec Burks SG 27 UTA 17 0 269 47 114 0.412 16 43
## 100 Alec Burks SG 27 CLE 34 24 979 136 340 0.400 45 119
## 101 Alec Burks SG 27 TOT 64 24 1375 192 474 0.405 61 168
## 102 Deonte Burton SG 25 OKC 32 0 240 33 82 0.402 8 27
## 103 Jimmy Butler SG 29 MIN 10 10 361 74 157 0.471 17 45
## 104 Jimmy Butler SF 29 PHI 55 55 1824 344 747 0.461 50 148
## 105 Jimmy Butler SF-SG 29 TOT 65 65 2185 418 904 0.462 67 193
## 106 Bruno Caboclo SF 23 MEM 34 19 800 96 225 0.427 48 130
## 107 Jose Calderon PG 37 DET 49 0 632 45 120 0.375 14 57
## 108 Kentavious Caldwell-Pope SG 25 LAL 82 23 2035 325 756 0.430 151 435
## 109 Isaiah Canaan PG 27 MIL 4 0 31 2 6 0.333 2 5
## 110 Isaiah Canaan PG 27 MIN 7 1 95 11 29 0.379 7 19
## 111 Isaiah Canaan PG 27 PHO 19 15 503 51 129 0.395 25 72
## 112 Isaiah Canaan PG 27 TOT 30 16 629 64 164 0.390 34 96
## 113 Clint Capela C 24 HOU 67 67 2249 474 732 0.648 0 0
## 114 DeMarre Carroll PF 32 BRK 67 8 1703 227 575 0.395 106 310
## 115 Jevon Carter PG 23 MEM 39 3 577 56 185 0.303 34 102
## 116 Vince Carter PF 42 ATL 76 9 1330 196 468 0.419 123 316
## 117 Wendell Carter C 19 CHI 44 44 1110 180 371 0.485 6 32
## 118 Michael Carter-Williams PG 27 ORL 12 0 227 21 62 0.339 3 19
## 119 Michael Carter-Williams PG 27 HOU 16 1 145 25 61 0.410 7 19
## 120 Michael Carter-Williams PG 27 TOT 28 1 372 46 123 0.374 10 38
## 121 Alex Caruso PG 24 LAL 25 4 531 77 173 0.445 24 50
## 122 Omri Casspi SF 30 MEM 36 0 520 86 161 0.534 15 43
## 123 Willie Cauley-Stein C 25 SAC 81 81 2213 412 741 0.556 1 2
## 124 Troy Caupain PG 23 ORL 4 0 16 4 8 0.500 2 3
## 125 Tyler Cavanaugh PF 24 UTA 11 0 39 3 10 0.300 1 5
## 126 Tyson Chandler C 36 PHO 7 0 89 8 12 0.667 0 0
## 127 Tyson Chandler C 36 LAL 48 6 786 53 87 0.609 0 1
## 128 Tyson Chandler C 36 TOT 55 6 875 61 99 0.616 0 1
## 129 Wilson Chandler SF 31 LAC 15 1 226 23 66 0.348 13 40
## 130 Wilson Chandler PF 31 PHI 36 32 951 91 207 0.440 46 118
## 131 Wilson Chandler PF-SF 31 TOT 51 33 1177 114 273 0.418 59 158
## 132 Joe Chealey PG 23 CHO 1 0 8 1 3 0.333 0 0
## 133 Chris Chiozza PG 23 HOU 7 0 33 2 8 0.250 2 5
## 134 Marquese Chriss PF 21 HOU 16 0 104 11 34 0.324 1 15
## 135 Marquese Chriss PF 21 CLE 27 2 395 56 146 0.384 15 57
## 136 Marquese Chriss PF 21 TOT 43 2 499 67 180 0.372 16 72
## 137 Gary Clark PF 24 HOU 51 2 641 50 151 0.331 41 138
## 138 Ian Clark SG 27 NOP 60 6 973 151 383 0.394 66 202
## 139 Jordan Clarkson SG 26 CLE 81 0 2214 529 1180 0.448 144 445
## 140 John Collins PF 21 ATL 61 59 1829 465 831 0.560 55 158
## 141 Zach Collins C 21 POR 77 0 1356 189 400 0.473 40 121
## 142 Darren Collison PG 31 IND 76 76 2143 308 659 0.467 79 194
## 143 Bonzie Colson SF 23 MIL 8 2 98 13 39 0.333 5 21
## 144 Mike Conley PG 31 MEM 70 70 2342 490 1120 0.438 155 426
## 145 Pat Connaughton SG 26 MIL 61 2 1261 163 350 0.466 66 200
## 146 Quinn Cook PG 25 GSW 74 10 1059 204 439 0.465 81 200
## 147 DeMarcus Cousins C 28 GSW 30 30 771 178 371 0.480 26 95
## 148 Robert Covington SF 28 PHI 13 13 440 50 117 0.427 30 77
## 149 Robert Covington SF 28 MIN 22 22 763 106 245 0.433 55 148
## 150 Robert Covington SF 28 TOT 35 35 1203 156 362 0.431 85 225
## 151 Allen Crabbe SG 26 BRK 43 20 1133 137 373 0.367 98 259
## 152 Torrey Craig SF 28 DEN 75 37 1503 160 362 0.442 61 188
## 153 Jamal Crawford SG 38 PHO 64 0 1211 174 438 0.397 67 202
## 154 Mitch Creek SF 26 MIN 1 0 12 3 6 0.500 0 1
## 155 Mitch Creek SF 26 BRK 4 0 36 5 10 0.500 0 1
## 156 Mitch Creek SF 26 TOT 5 0 48 8 16 0.500 0 2
## 157 Jae Crowder SF 28 UTA 80 11 2166 318 797 0.399 173 522
## 158 Dante Cunningham PF 31 SAS 64 21 928 75 158 0.475 30 65
## 159 Seth Curry SG 28 POR 74 2 1399 212 465 0.456 113 251
## 160 Stephen Curry PG 30 GSW 69 69 2331 632 1340 0.472 354 810
## 161 Troy Daniels SG 27 PHO 51 1 760 113 275 0.411 74 194
## 162 Anthony Davis C 25 NOP 56 56 1850 530 1026 0.517 48 145
## 163 Deyonta Davis C 22 ATL 9 0 118 15 22 0.682 0 1
## 164 Ed Davis C 29 BRK 81 1 1446 186 302 0.616 0 2
## 165 Tyler Davis C 21 OKC 1 0 1 0 1 0.000 0 0
## 166 Dewayne Dedmon C 29 ATL 64 52 1609 259 526 0.492 83 217
## 167 Sam Dekker PF 24 CLE 9 5 169 22 48 0.458 5 13
## 168 Sam Dekker PF 24 WAS 38 0 619 98 208 0.471 14 49
## 169 Sam Dekker PF 24 TOT 47 5 788 120 256 0.469 19 62
## 170 Angel Delgado C 24 LAC 2 0 15 1 5 0.200 0 0
## 171 Matthew Dellavedova PG 28 MIL 12 0 97 6 19 0.316 4 11
## 172 Matthew Dellavedova PG 28 CLE 36 0 715 92 223 0.413 40 119
## 173 Matthew Dellavedova PG 28 TOT 48 0 812 98 242 0.405 44 130
## 174 Luol Deng SF 33 MIN 22 2 392 59 118 0.500 14 44
## 175 DeMar DeRozan SG 29 SAS 77 77 2688 631 1313 0.481 7 45
## 176 Marcus Derrickson PF 22 GSW 11 0 67 16 33 0.485 10 20
## 177 Cheick Diallo PF 22 NOP 64 1 896 168 271 0.620 1 4
## 178 Hamidou Diallo SG 20 OKC 51 3 526 75 165 0.455 4 24
## 179 Gorgui Dieng C 29 MIN 76 2 1031 189 377 0.501 19 56
## 180 Spencer Dinwiddie PG 25 BRK 68 4 1914 366 828 0.442 124 370
## 181 Donte DiVincenzo SG 22 MIL 27 0 411 50 124 0.403 22 83
## 182 Luka Doncic SG 19 DAL 72 72 2318 506 1186 0.427 168 514
## 183 Tyler Dorsey SG 22 ATL 27 0 251 32 89 0.360 10 39
## 184 Tyler Dorsey SG 22 MEM 21 11 447 75 175 0.429 34 93
## 185 Tyler Dorsey SG 22 TOT 48 11 698 107 264 0.405 44 132
## 186 Damyean Dotson SG 24 NYK 73 40 2004 290 698 0.415 126 342
## 187 PJ Dozier SG 22 BOS 6 0 51 8 21 0.381 2 8
## 188 Goran Dragic PG 32 MIA 36 22 991 179 433 0.413 57 164
## 189 Andre Drummond C 25 DET 79 79 2647 561 1052 0.533 5 38
## 190 Jared Dudley PF 33 BRK 59 25 1220 101 239 0.423 53 151
## 191 Kris Dunn PG 24 CHI 46 44 1389 215 506 0.425 34 96
## 192 Kevin Durant SF 30 GSW 78 78 2702 721 1383 0.521 137 388
## 193 Trevon Duval PG 20 MIL 3 0 6 2 3 0.667 1 1
## 194 Vince Edwards SF 22 HOU 2 0 16 1 4 0.250 1 4
## 195 Henry Ellenson PF 22 DET 2 0 25 4 10 0.400 2 4
## 196 Henry Ellenson PF 22 NYK 17 0 234 35 85 0.412 15 34
## 197 Henry Ellenson PF 22 TOT 19 0 259 39 95 0.411 17 38
## 198 Wayne Ellington SG 31 MIA 25 12 533 69 184 0.375 57 155
## 199 Wayne Ellington SG 31 DET 28 26 764 115 273 0.421 81 217
## 200 Wayne Ellington SG 31 TOT 53 38 1297 184 457 0.403 138 372
## 201 Joel Embiid C 24 PHI 64 64 2154 580 1199 0.484 79 263
## 202 James Ennis SF 28 PHI 18 2 281 34 83 0.410 11 36
## 203 James Ennis SF 28 HOU 40 25 949 104 211 0.493 44 120
## 204 James Ennis SF 28 TOT 58 27 1230 138 294 0.469 55 156
## 205 Drew Eubanks PF 21 SAS 23 0 113 15 26 0.577 0 0
## 206 Jacob Evans SG 21 GSW 30 1 204 18 53 0.340 4 15
## 207 Jawun Evans PG 22 OKC 1 0 1 0 1 0.000 0 1
## 208 Jawun Evans PG 22 TOT 8 0 65 3 14 0.214 0 3
## 209 Jawun Evans PG 22 PHO 7 0 64 3 13 0.231 0 2
## 210 Tyreke Evans SG 29 IND 69 18 1402 257 660 0.389 77 216
## 211 Dante Exum PG 23 UTA 42 1 664 101 241 0.419 18 62
## 212 Kenneth Faried C 29 BRK 12 0 118 25 42 0.595 1 5
## 213 Kenneth Faried C 29 HOU 25 13 610 131 223 0.587 7 20
## 214 Kenneth Faried C 29 TOT 37 13 728 156 265 0.589 8 25
## 215 Derrick Favors C 27 UTA 76 70 1766 363 619 0.586 17 78
## 216 Raymond Felton PG 34 OKC 33 0 379 55 135 0.407 20 61
## 217 Cristiano Felicio C 26 CHI 60 0 746 95 179 0.531 0 4
## 218 Terrance Ferguson SG 20 OKC 74 74 1931 185 431 0.429 106 290
## 219 Yogi Ferrell PG 25 SAC 71 3 1067 153 352 0.435 54 149
## 220 Dorian Finney-Smith SF 25 DAL 81 26 1985 228 528 0.432 79 254
## 221 Bryn Forbes SG 25 SAS 82 81 2293 361 791 0.456 176 413
## 222 Evan Fournier SG 26 ORL 81 81 2553 468 1069 0.438 153 450
## 223 De'Aaron Fox PG 21 SAC 81 81 2546 505 1102 0.458 86 232
## 224 Melvin Frazier SG 22 ORL 10 0 44 7 21 0.333 0 6
## 225 Tim Frazier PG 28 MIL 12 2 211 28 66 0.424 10 24
## 226 Tim Frazier PG 28 NOP 47 17 909 88 195 0.451 27 77
## 227 Tim Frazier PG 28 TOT 59 19 1120 116 261 0.444 37 101
## 228 Jimmer Fredette SG 29 PHO 6 0 65 8 29 0.276 0 13
## 229 Channing Frye C 35 CLE 36 6 341 43 117 0.368 32 79
## 230 Markelle Fultz SG 20 PHI 19 15 427 65 155 0.419 4 14
## 231 Danilo Gallinari SF 30 LAC 68 68 2059 409 884 0.463 161 372
## 232 Langston Galloway SG 27 DET 80 4 1745 228 587 0.388 135 380
## 233 Billy Garrett SG 24 NYK 4 0 63 11 27 0.407 0 8
## 234 Marc Gasol C 34 TOR 26 19 648 87 187 0.465 23 52
## 235 Marc Gasol C 34 MEM 53 53 1788 303 683 0.444 76 221
## 236 Marc Gasol C 34 TOT 79 72 2436 390 870 0.448 99 273
## 237 Pau Gasol C 38 MIL 3 0 30 1 6 0.167 1 3
## 238 Pau Gasol C 38 SAS 27 6 330 41 88 0.466 5 10
## 239 Pau Gasol C 38 TOT 30 6 360 42 94 0.447 6 13
## 240 Rudy Gay PF 32 SAS 69 51 1842 376 746 0.504 74 184
## 241 Paul George SF 28 OKC 77 77 2841 707 1614 0.438 292 757
## 242 Taj Gibson PF 33 MIN 70 57 1686 304 537 0.566 11 34
## 243 Harry Giles PF 20 SAC 58 0 820 175 348 0.503 0 6
## 244 Shai Gilgeous-Alexander PG 20 LAC 82 73 2174 341 716 0.476 51 139
## 245 Rudy Gobert C 26 UTA 81 80 2577 476 712 0.669 0 0
## 246 Brandon Goodwin PG 23 DEN 16 0 57 6 23 0.261 2 6
## 247 Aaron Gordon PF 23 ORL 78 78 2633 470 1046 0.449 121 347
## 248 Eric Gordon SG 30 HOU 68 53 2158 384 938 0.409 216 600
## 249 Marcin Gortat C 34 LAC 47 43 751 99 186 0.532 0 0
## 250 Devonte' Graham PG 23 CHO 46 3 676 74 216 0.343 34 121
## 251 Treveon Graham SG 25 BRK 35 21 715 64 191 0.335 38 128
## 252 Jerami Grant PF 24 OKC 80 77 2612 409 823 0.497 115 293
## 253 Jerian Grant PG 26 ORL 60 1 939 92 220 0.418 40 110
## 254 Donte Grantham SF 23 OKC 3 0 2 0 2 0.000 0 2
## 255 Danny Green SG 31 TOR 80 80 2216 293 630 0.465 198 435
## 256 Draymond Green PF 28 GSW 66 66 2065 188 422 0.445 47 165
## 257 Gerald Green SG 33 HOU 73 0 1473 231 578 0.400 156 441
## 258 JaMychal Green PF 28 LAC 24 2 471 79 164 0.482 33 80
## 259 JaMychal Green PF 28 MEM 41 4 900 151 312 0.484 38 96
## 260 JaMychal Green PF 28 TOT 65 6 1371 230 476 0.483 71 176
## 261 Jeff Green PF 32 WAS 77 44 2097 326 687 0.475 111 320
## 262 Blake Griffin PF 29 DET 75 75 2622 619 1341 0.462 189 522
## 263 Daniel Hamilton SG 23 ATL 19 3 204 23 60 0.383 8 23
## 264 Dusty Hannahs SG 25 MEM 2 0 26 3 12 0.250 0 5
## 265 Tim Hardaway SG 26 DAL 19 17 558 108 267 0.404 45 140
## 266 Tim Hardaway SG 26 NYK 46 46 1499 282 726 0.388 117 337
## 267 Tim Hardaway SG 26 TOT 65 63 2057 390 993 0.393 162 477
## 268 James Harden PG 29 HOU 78 78 2867 843 1909 0.442 378 1028
## 269 Maurice Harkless SF 25 POR 60 53 1415 189 388 0.487 33 120
## 270 Montrezl Harrell C 25 LAC 82 5 2158 546 888 0.615 3 17
## 271 Devin Harris PG 35 DAL 68 2 1071 132 347 0.380 62 200
## 272 Gary Harris SG 24 DEN 57 48 1639 270 637 0.424 82 242
## 273 Joe Harris SG 27 BRK 76 76 2293 374 748 0.500 183 386
## 274 Tobias Harris PF 26 PHI 27 27 944 187 399 0.469 44 135
## 275 Tobias Harris PF 26 LAC 55 55 1903 424 855 0.496 112 258
## 276 Tobias Harris PF 26 TOT 82 82 2847 611 1254 0.487 156 393
## 277 Andrew Harrison PG 24 MEM 1 0 5 1 2 0.500 0 1
## 278 Andrew Harrison PG 24 NOP 6 0 38 3 12 0.250 2 10
## 279 Andrew Harrison PG 24 CLE 10 0 144 12 39 0.308 3 14
## 280 Andrew Harrison PG 24 TOT 17 0 187 16 53 0.302 5 25
## 281 Shaquille Harrison PG 25 CHI 73 11 1430 184 426 0.432 24 89
## 282 Josh Hart SG 23 LAL 67 22 1715 189 464 0.407 92 274
## 283 Isaiah Hartenstein PF 20 HOU 28 0 221 20 41 0.488 2 6
## 284 Udonis Haslem C 38 MIA 10 1 74 11 33 0.333 0 12
## 285 Gordon Hayward PF 28 BOS 72 18 1863 296 635 0.466 77 231
## 286 John Henson C 28 MIL 14 0 188 31 67 0.463 11 31
## 287 Juan Hernangomez PF 23 DEN 70 25 1358 138 314 0.439 66 181
## 288 Willy Hernangomez C 24 CHO 58 3 812 153 295 0.519 15 39
## 289 Mario Hezonja SF 23 NYK 58 24 1206 191 464 0.412 42 152
## 290 Isaiah Hicks PF 24 NYK 3 0 32 4 8 0.500 0 0
## 291 Buddy Hield SG 26 SAC 82 82 2615 623 1360 0.458 278 651
## 292 Haywood Highsmith SF 22 PHI 5 0 40 4 10 0.400 1 5
## 293 George Hill PG 32 CLE 13 13 344 55 107 0.514 13 28
## 294 George Hill PG 32 MIL 47 0 958 115 269 0.428 35 125
## 295 George Hill PG 32 TOT 60 13 1302 170 376 0.452 48 153
## 296 Solomon Hill SF 27 NOP 44 15 878 68 178 0.382 32 101
## 297 Nene Hilario C 36 HOU 42 2 546 60 116 0.517 0 3
## 298 Aaron Holiday PG 22 IND 50 0 646 105 262 0.401 43 127
## 299 Jrue Holiday SG 28 NOP 67 67 2402 547 1159 0.472 118 363
## 300 Justin Holiday SG 29 MEM 44 39 1282 149 383 0.389 65 195
## 301 Justin Holiday SG 29 CHI 38 38 1325 151 394 0.383 97 270
## 302 Justin Holiday SG 29 TOT 82 77 2607 300 777 0.386 162 465
## 303 John Holland SF 30 CLE 1 0 1 0 0 NA 0 0
## 304 Rondae Hollis-Jefferson SF 24 BRK 59 21 1234 200 487 0.411 9 49
## 305 Richaun Holmes C 25 PHO 70 4 1184 222 365 0.608 0 0
## 306 Rodney Hood SG 26 POR 27 4 659 98 217 0.452 29 84
## 307 Rodney Hood SG 26 CLE 45 45 1234 194 454 0.427 55 152
## 308 Rodney Hood SG 26 TOT 72 49 1893 292 671 0.435 84 236
## 309 Al Horford C 32 BOS 68 68 1973 387 723 0.535 73 203
## 310 Danuel House SF 25 HOU 39 13 979 118 252 0.468 74 178
## 311 Dwight Howard C 33 WAS 9 9 230 43 69 0.623 0 0
## 312 Kevin Huerter SG 20 ATL 75 59 2048 275 657 0.419 136 353
## 313 Isaac Humphries C 21 ATL 5 1 56 6 21 0.286 3 11
## 314 RJ Hunter SG 25 BOS 1 0 26 6 13 0.462 4 10
## 315 Chandler Hutchison SF 22 CHI 44 14 895 96 209 0.459 14 50
## 316 Serge Ibaka C 29 TOR 74 51 2010 464 877 0.529 49 169
## 317 Andre Iguodala SF 35 GSW 68 13 1578 151 302 0.500 48 144
## 318 Joe Ingles PF 31 UTA 82 82 2568 359 802 0.448 189 483
## 319 Andre Ingram SG 33 LAL 4 0 15 0 6 0.000 0 3
## 320 Brandon Ingram SF 21 LAL 52 52 1760 362 729 0.497 31 94
## 321 Kyrie Irving PG 26 BOS 67 67 2214 604 1241 0.487 174 434
## 322 Jonathan Isaac PF 21 ORL 75 64 1996 262 611 0.429 86 266
## 323 Wesley Iwundu SF 24 ORL 68 13 1233 113 274 0.412 29 79
## 324 Ersan Ilyasova PF 31 MIL 67 7 1231 167 381 0.438 58 160
## 325 Demetrius Jackson PG 24 PHI 6 0 39 8 15 0.533 2 6
## 326 Frank Jackson PG 20 NOP 61 16 1169 194 447 0.434 53 169
## 327 Jaren Jackson PF 19 MEM 58 56 1515 298 589 0.506 51 142
## 328 Josh Jackson SG 21 PHO 79 29 1988 347 841 0.413 73 225
## 329 Justin Jackson SF 23 DAL 29 11 531 92 190 0.484 32 86
## 330 Justin Jackson SF 23 SAC 52 3 1083 125 295 0.424 55 159
## 331 Justin Jackson SF 23 TOT 81 14 1614 217 485 0.447 87 245
## 332 Reggie Jackson PG 28 DET 82 82 2289 441 1047 0.421 174 471
## 333 LeBron James SF 34 LAL 55 55 1937 558 1095 0.510 111 327
## 334 Amile Jefferson PF 25 ORL 12 0 68 10 16 0.625 0 0
## 335 John Jenkins SG 27 WAS 4 0 14 2 2 1.000 2 2
## 336 John Jenkins SG 27 NYK 22 0 319 40 103 0.388 20 56
## 337 John Jenkins SG 27 TOT 26 0 333 42 105 0.400 22 58
## 338 Jonas Jerebko PF 31 GSW 73 6 1218 163 355 0.459 69 188
## 339 Alize Johnson PF 22 IND 14 0 64 4 16 0.250 1 2
## 340 Amir Johnson C 31 PHI 51 6 529 79 157 0.503 12 40
## 341 BJ Johnson SF 23 SAC 1 0 6 1 2 0.500 0 1
## 342 BJ Johnson SF 23 ATL 6 0 43 8 16 0.500 3 6
## 343 BJ Johnson SF 23 TOT 7 0 49 9 18 0.500 3 7
## 344 James Johnson PF 31 MIA 55 33 1164 164 379 0.433 50 149
## 345 Stanley Johnson SF 22 NOP 18 0 247 38 91 0.418 11 34
## 346 Stanley Johnson SF 22 DET 48 7 961 133 349 0.381 51 181
## 347 Stanley Johnson SF 22 TOT 66 7 1208 171 440 0.389 62 215
## 348 Tyler Johnson PG 26 PHO 13 12 406 46 125 0.368 18 56
## 349 Tyler Johnson PG 26 MIA 44 10 1123 171 401 0.426 72 204
## 350 Tyler Johnson PG 26 TOT 57 22 1529 217 526 0.413 90 260
## 351 Wesley Johnson SF 31 WAS 12 0 157 10 40 0.250 6 26
## 352 Wesley Johnson SF 31 NOP 26 13 377 35 88 0.398 19 50
## 353 Wesley Johnson SF 31 TOT 38 13 534 45 128 0.352 25 76
## 354 Nikola Jokic C 23 DEN 80 80 2504 616 1206 0.511 83 270
## 355 Damian Jones C 23 GSW 24 22 410 53 74 0.716 0 0
## 356 Derrick Jones SF 21 MIA 60 14 1153 160 324 0.494 28 91
## 357 Jalen Jones SF 25 CLE 16 0 214 26 62 0.419 10 28
## 358 Jemerrio Jones SF 23 LAL 6 2 143 12 33 0.364 2 10
## 359 Terrence Jones PF 27 HOU 2 0 5 1 4 0.250 0 2
## 360 Tyus Jones PG 22 MIN 68 23 1560 185 446 0.415 40 126
## 361 DeAndre Jordan C 30 NYK 19 19 493 78 123 0.634 0 0
## 362 DeAndre Jordan C 30 DAL 50 50 1554 208 323 0.644 0 0
## 363 DeAndre Jordan C 30 TOT 69 69 2047 286 446 0.641 0 0
## 364 Cory Joseph PG 27 IND 82 9 2063 226 548 0.412 55 171
## 365 Frank Kaminsky C 25 CHO 47 0 755 138 298 0.463 50 139
## 366 Enes Kanter C 26 POR 23 8 512 124 215 0.577 3 12
## 367 Enes Kanter C 26 NYK 44 23 1128 251 468 0.536 7 22
## 368 Enes Kanter C 26 TOT 67 31 1640 375 683 0.549 10 34
## 369 Luke Kennard SG 22 DET 63 10 1437 228 520 0.438 106 269
## 370 Michael Kidd-Gilchrist PF 25 CHO 64 3 1179 158 332 0.476 16 47
## 371 George King SF 25 PHO 1 0 6 0 0 NA 0 0
## 372 Maxi Kleber PF 27 DAL 71 18 1502 175 386 0.453 77 218
## 373 Brandon Knight PG 27 HOU 12 0 118 11 47 0.234 5 32
## 374 Brandon Knight PG 27 CLE 27 26 618 88 213 0.413 36 97
## 375 Brandon Knight PG 27 TOT 39 26 736 99 260 0.381 41 129
## 376 Kevin Knox PF 19 NYK 75 57 2158 338 914 0.370 125 364
## 377 Furkan Korkmaz SG 21 PHI 48 7 679 98 245 0.400 47 144
## 378 Luke Kornet PF 23 NYK 46 18 784 107 283 0.378 70 193
## 379 Kyle Korver PF 37 CLE 16 0 251 35 76 0.461 25 54
## 380 Kyle Korver SG 37 UTA 54 0 1083 166 407 0.408 113 294
## 381 Kyle Korver SG-PF 37 TOT 70 0 1334 201 483 0.416 138 348
## 382 Kosta Koufos C 29 SAC 42 1 502 73 153 0.477 0 0
## 383 Rodions Kurucs SF 20 BRK 63 46 1294 202 449 0.450 58 184
## 384 Kyle Kuzma PF 23 LAL 70 68 2314 496 1087 0.456 128 422
## 385 Skal Labissiere PF 22 POR 9 1 63 13 19 0.684 2 2
## 386 Skal Labissiere PF 22 SAC 13 0 113 13 30 0.433 4 11
## 387 Skal Labissiere PF 22 TOT 22 1 176 26 49 0.531 6 13
## 388 Jeremy Lamb SG 26 CHO 79 55 2250 431 979 0.440 115 330
## 389 Zach LaVine SG 23 CHI 63 62 2171 530 1135 0.467 120 321
## 390 Jake Layman SF 24 POR 71 33 1327 216 424 0.509 59 181
## 391 TJ Leaf PF 21 IND 58 1 522 99 183 0.541 8 31
## 392 Courtney Lee SG 33 NYK 12 2 160 21 47 0.447 5 16
## 393 Courtney Lee SG 33 DAL 22 4 268 32 82 0.390 11 39
## 394 Courtney Lee SG 33 TOT 34 6 428 53 129 0.411 16 55
## 395 Damion Lee SG 26 GSW 32 0 375 56 127 0.441 27 68
## 396 Walt Lemon PG 26 CHI 6 3 167 38 87 0.437 2 5
## 397 Alex Len C 25 ATL 77 31 1544 320 648 0.494 74 204
## 398 Kawhi Leonard SF 27 TOR 60 60 2040 560 1129 0.496 112 302
## 399 Meyers Leonard C 26 POR 61 2 878 132 242 0.545 50 111
## 400 Jon Leuer PF 29 DET 41 1 402 66 113 0.584 1 11
## 401 Caris LeVert SF 24 BRK 40 25 1063 207 483 0.429 48 154
## 402 Damian Lillard PG 28 POR 80 80 2838 681 1533 0.444 237 643
## 403 Jeremy Lin PG 30 TOR 23 3 433 58 155 0.374 11 55
## 404 Jeremy Lin PG 30 ATL 51 1 1003 180 386 0.466 44 132
## 405 Jeremy Lin PG 30 TOT 74 4 1436 238 541 0.440 55 187
## 406 Shaun Livingston PG 33 GSW 64 0 967 109 210 0.519 0 2
## 407 Zach Lofton SG 26 DET 1 0 4 0 1 0.000 0 1
## 408 Kevon Looney C 22 GSW 80 24 1481 217 347 0.625 1 10
## 409 Brook Lopez C 30 MIL 81 81 2322 355 786 0.452 187 512
## 410 Robin Lopez C 30 CHI 74 36 1606 304 535 0.568 7 31
## 411 Kevin Love PF 30 CLE 22 21 598 109 283 0.385 53 147
## 412 Kyle Lowry PG 32 TOR 65 65 2213 304 739 0.411 157 453
## 413 Jordan Loyd PG 25 TOR 12 0 55 8 18 0.444 4 8
## 414 Kalin Lucas PG 29 DET 1 0 6 0 1 0.000 0 1
## 415 Timothe Luwawu-Cabarrot SF 23 OKC 21 1 123 13 43 0.302 5 22
## 416 Timothe Luwawu-Cabarrot SF 23 CHI 29 6 546 69 175 0.394 31 94
## 417 Timothe Luwawu-Cabarrot SF 23 TOT 50 7 669 82 218 0.376 36 116
## 418 Tyler Lydon PF 22 DEN 25 0 94 9 18 0.500 4 10
## 419 Trey Lyles PF 23 DEN 64 2 1120 207 495 0.418 51 200
## 420 Scott Machado PG 28 LAL 4 0 19 4 6 0.667 1 1
## 421 Shelvin Mack PG 28 CHO 4 0 42 2 14 0.143 0 2
## 422 Shelvin Mack PG 28 MEM 53 3 1204 161 389 0.414 46 128
## 423 Shelvin Mack PG 28 TOT 57 3 1246 163 403 0.404 46 130
## 424 Daryl Macon SG 23 DAL 8 0 90 10 27 0.370 5 11
## 425 JP Macura SG 23 CHO 2 0 17 3 9 0.333 0 4
## 426 Ian Mahinmi C 32 WAS 34 6 498 47 104 0.452 3 16
## 427 Thon Maker PF 21 DET 29 5 563 50 134 0.373 23 75
## 428 Thon Maker C 21 MIL 35 0 409 59 134 0.440 26 78
## 429 Thon Maker C-PF 21 TOT 64 5 972 109 268 0.407 49 153
## 430 Boban Marjanovic C 30 PHI 22 3 305 75 120 0.625 4 8
## 431 Boban Marjanovic C 30 LAC 36 9 376 85 140 0.607 0 2
## 432 Boban Marjanovic C 30 TOT 58 12 681 160 260 0.615 4 10
## 433 Lauri Markkanen PF 21 CHI 52 51 1682 342 795 0.430 120 332
## 434 Jarell Martin PF 24 ORL 42 1 328 43 104 0.413 20 57
## 435 Frank Mason PG 24 SAC 38 0 435 71 169 0.420 14 64
## 436 Yante Maten PF 22 MIA 2 0 13 1 4 0.250 0 1
## 437 Wesley Matthews SG 32 NYK 2 1 54 4 19 0.211 2 10
## 438 Wesley Matthews SG 32 IND 23 23 725 81 210 0.386 48 130
## 439 Wesley Matthews SF 32 DAL 44 44 1312 194 469 0.414 100 263
## 440 Wesley Matthews SF-SG 32 TOT 69 68 2091 279 698 0.400 150 403
## 441 Luc Mbah a Moute PF 32 LAC 4 0 61 8 18 0.444 2 6
## 442 Tahjere McCall SG 24 BRK 1 0 8 2 3 0.667 0 1
## 443 Patrick McCaw SG 23 CLE 3 0 53 2 9 0.222 1 4
## 444 Patrick McCaw SG 23 TOR 26 1 344 24 54 0.444 8 24
## 445 Patrick McCaw SG 23 TOT 29 1 397 26 63 0.413 9 28
## 446 CJ McCollum SG 27 POR 70 70 2375 571 1243 0.459 167 445
## 447 TJ McConnell PG 26 PHI 76 3 1470 220 419 0.525 14 42
## 448 Doug McDermott SF 27 IND 77 1 1340 207 422 0.491 84 206
## 449 JaVale McGee C 31 LAL 75 62 1671 400 641 0.624 1 12
## 450 Rodney McGruder SG 27 MIA 66 45 1550 186 461 0.403 79 225
## 451 Alfonzo McKinnie SF 26 GSW 72 5 1003 134 275 0.487 42 118
## 452 Ben McLemore SG 25 SAC 19 0 158 25 64 0.391 17 41
## 453 Jordan McRae SG 27 WAS 27 0 333 61 130 0.469 10 35
## 454 Jodie Meeks SG 31 TOR 8 0 104 21 39 0.538 8 18
## 455 Salah Mejri C 32 DAL 36 4 399 55 112 0.491 11 34
## 456 De'Anthony Melton PG 20 PHO 50 31 984 100 256 0.391 29 95
## 457 Chimezie Metu PF 21 SAS 29 0 145 19 58 0.328 0 2
## 458 Khris Middleton SF 27 MIL 77 77 2393 506 1148 0.441 179 474
## 459 CJ Miles SF 31 MEM 13 0 294 42 105 0.400 24 66
## 460 CJ Miles SF 31 TOR 40 1 562 70 206 0.340 43 137
## 461 CJ Miles SF 31 TOT 53 1 856 112 311 0.360 67 203
## 462 Darius Miller SF 28 NOP 69 15 1757 189 484 0.390 133 364
## 463 Malcolm Miller SF 25 TOR 10 0 67 11 26 0.423 10 21
## 464 Patty Mills PG 30 SAS 82 1 1908 282 663 0.425 159 404
## 465 Paul Millsap PF 33 DEN 70 65 1895 322 665 0.484 58 159
## 466 Shake Milton SG 22 PHI 20 0 268 34 87 0.391 14 44
## 467 Nikola Mirotic PF 27 MIL 14 3 320 56 135 0.415 31 87
## 468 Nikola Mirotic PF 27 NOP 32 22 925 182 407 0.447 85 231
## 469 Nikola Mirotic PF 27 TOT 46 25 1245 238 542 0.439 116 318
## 470 Donovan Mitchell SG 22 UTA 77 77 2598 661 1530 0.432 188 519
## 471 Naz Mitrou-Long SG 25 UTA 14 0 84 6 20 0.300 2 11
## 472 Malik Monk SG 20 CHO 73 0 1258 227 586 0.387 109 330
## 473 Greg Monroe C 28 BOS 2 0 5 3 5 0.600 0 0
## 474 Greg Monroe C 28 PHI 3 0 52 15 23 0.652 1 1
## 475 Greg Monroe C 28 TOR 38 2 423 74 161 0.460 0 4
## 476 Greg Monroe C 28 TOT 43 2 480 92 189 0.487 1 5
## 477 E'Twaun Moore SG 29 NOP 53 36 1463 256 532 0.481 76 176
## 478 Eric Moreland PF 27 PHO 1 0 5 0 0 NA 0 0
## 479 Eric Moreland PF 27 TOT 5 0 43 3 7 0.429 1 1
## 480 Eric Moreland PF 27 TOR 4 0 38 3 7 0.429 1 1
## 481 Jaylen Morris SG 23 MIL 4 0 29 4 10 0.400 1 3
## 482 Marcus Morris PF 29 BOS 75 53 2091 377 844 0.447 146 389
## 483 Markieff Morris PF 29 OKC 24 1 387 61 156 0.391 20 59
## 484 Markieff Morris PF 29 WAS 34 15 883 143 328 0.436 48 144
## 485 Markieff Morris PF 29 TOT 58 16 1270 204 484 0.421 68 203
## 486 Monte Morris PG 23 DEN 82 6 1970 346 702 0.493 94 227
## 487 Donatas Motiejunas PF 28 SAS 3 0 13 3 6 0.500 0 0
## 488 Johnathan Motley PF 23 LAC 22 0 156 39 73 0.534 0 3
## 489 Emmanuel Mudiay PG 22 NYK 59 42 1607 330 740 0.446 69 210
## 490 Jamal Murray PG 21 DEN 75 74 2447 513 1173 0.437 152 414
## 491 Dzanan Musa SG 19 BRK 9 0 39 9 22 0.409 1 10
## 492 Mike Muscala PF 27 LAL 17 4 265 36 83 0.434 21 57
## 493 Mike Muscala PF 27 PHI 47 6 1041 109 278 0.392 68 199
## 494 Mike Muscala PF 27 TOT 64 10 1306 145 361 0.402 89 256
## 495 Sviatoslav Mykhailiuk SF 21 DET 3 0 20 2 8 0.250 2 4
## 496 Sviatoslav Mykhailiuk SF 21 LAL 39 0 420 44 132 0.333 27 85
## 497 Sviatoslav Mykhailiuk SF 21 TOT 42 0 440 46 140 0.329 29 89
## 498 Abdel Nader SF 25 OKC 61 1 694 91 215 0.423 32 100
## 499 Larry Nance C 26 CLE 67 30 1795 249 479 0.520 33 98
## 500 Shabazz Napier PG 27 BRK 56 2 983 169 435 0.389 76 228
## 501 Raul Neto PG 26 UTA 37 1 474 74 161 0.460 20 60
## 502 Georges Niang PF 25 UTA 59 0 516 86 181 0.475 43 105
## 503 Joakim Noah C 33 MEM 42 1 693 110 213 0.516 0 1
## 504 Nerlens Noel C 24 OKC 77 2 1055 162 276 0.587 0 0
## 505 Dirk Nowitzki PF 40 DAL 51 20 795 135 376 0.359 64 205
## 506 Frank Ntilikina PG 20 NYK 43 16 904 95 282 0.337 33 115
## 507 James Nunnally SF 28 HOU 2 0 38 3 13 0.231 3 12
## 508 James Nunnally SF 28 MIN 13 0 64 9 21 0.429 5 13
## 509 James Nunnally SF 28 TOT 15 0 102 12 34 0.353 8 25
## 510 Jusuf Nurkic C 24 POR 72 72 1974 420 826 0.508 3 29
## 511 David Nwaba SG 26 CLE 51 14 984 126 262 0.481 24 75
## 512 Royce O'Neale SF 25 UTA 82 16 1671 163 343 0.475 68 176
## 513 Kyle O'Quinn C 28 IND 45 3 371 69 136 0.507 1 12
## 514 Semi Ojeleye PF 24 BOS 56 3 594 67 158 0.424 28 89
## 515 Jahlil Okafor C 23 NOP 59 24 935 212 362 0.586 1 5
## 516 Elie Okobo PG 21 PHO 53 16 958 114 290 0.393 39 132
## 517 Josh Okogie SG 20 MIN 74 52 1757 196 508 0.386 60 215
## 518 Victor Oladipo SG 26 IND 36 36 1147 249 588 0.423 74 216
## 519 Kelly Olynyk PF 27 MIA 79 36 1812 261 564 0.463 113 319
## 520 Cedi Osman SF 23 CLE 76 75 2444 360 844 0.427 130 374
## 521 Kelly Oubre SF 23 WAS 29 7 755 132 305 0.433 41 132
## 522 Kelly Oubre SF 23 PHO 40 12 1180 243 537 0.453 67 206
## 523 Kelly Oubre SF 23 TOT 69 19 1935 375 842 0.445 108 338
## 524 Zaza Pachulia C 34 DET 68 3 878 85 193 0.440 0 4
## 525 Jabari Parker PF 23 WAS 25 0 682 149 285 0.523 24 81
## 526 Jabari Parker PF 23 CHI 39 17 1042 220 464 0.474 37 114
## 527 Jabari Parker PF 23 TOT 64 17 1724 369 749 0.493 61 195
## 528 Tony Parker PG 36 CHO 56 0 1003 213 463 0.460 13 51
## 529 Chandler Parsons SF 30 MEM 25 3 496 68 182 0.374 29 94
## 530 Patrick Patterson PF 29 OKC 63 5 861 82 219 0.374 46 137
## 531 Justin Patton C 21 PHI 3 0 21 2 7 0.286 0 2
## 532 Chris Paul PG 33 HOU 58 58 1857 302 720 0.419 127 355
## 533 Cameron Payne PG 24 CLE 9 1 176 27 55 0.491 9 25
## 534 Cameron Payne PG 24 CHI 31 12 536 69 168 0.411 16 59
## 535 Cameron Payne PG 24 TOT 40 13 712 96 223 0.430 25 84
## 536 Elfrid Payton PG 24 NOP 42 42 1250 179 412 0.434 33 105
## 537 Gary Payton PG 26 WAS 3 0 16 5 8 0.625 1 2
## 538 Theo Pinson SG 23 BRK 18 0 211 25 73 0.342 12 46
## 539 Mason Plumlee C 28 DEN 82 17 1731 262 442 0.593 2 10
## 540 Miles Plumlee C 30 ATL 18 0 173 32 48 0.667 0 0
## 541 Quincy Pondexter SF 30 SAS 53 0 292 29 58 0.500 6 18
## 542 Otto Porter SF 25 CHI 15 15 492 97 201 0.483 39 80
## 543 Otto Porter SF 25 WAS 41 28 1191 202 442 0.457 65 176
## 544 Otto Porter SF 25 TOT 56 43 1683 299 643 0.465 104 256
## 545 Bobby Portis PF 23 CHI 22 6 531 122 271 0.450 27 72
## 546 Bobby Portis PF 23 WAS 28 22 768 157 357 0.440 48 119
## 547 Bobby Portis PF 23 TOT 50 28 1299 279 628 0.444 75 191
## 548 Dwight Powell C 27 DAL 77 22 1662 290 486 0.597 39 127
## 549 Norman Powell SG 25 TOR 60 3 1126 193 400 0.483 68 170
## 550 Alex Poythress PF 25 ATL 21 1 305 40 81 0.494 9 23
## 551 Jakob Poltl C 23 SAS 77 24 1273 187 290 0.645 0 0
## 552 Zhou Qi PF 23 HOU 1 0 1 1 1 1.000 0 0
## 553 Ivan Rabb PF 21 MEM 49 13 721 116 212 0.547 3 15
## 554 Chasson Randle PG 25 WAS 49 2 743 91 217 0.419 46 115
## 555 Julius Randle PF 24 NOP 73 49 2232 571 1089 0.524 67 195
## 556 JJ Redick SG 34 PHI 76 63 2379 452 1027 0.440 240 605
## 557 Davon Reed SG 23 IND 10 0 47 5 12 0.417 2 4
## 558 Cameron Reynolds SG 23 MIN 19 0 259 33 78 0.423 21 51
## 559 Josh Richardson SG 25 MIA 73 73 2539 423 1026 0.412 164 460
## 560 Malachi Richardson SG 23 TOR 22 0 103 9 29 0.310 8 25
## 561 Austin Rivers SG 26 WAS 29 2 683 76 194 0.392 33 106
## 562 Austin Rivers SG 26 HOU 47 13 1345 156 378 0.413 71 221
## 563 Austin Rivers SG 26 TOT 76 15 2028 232 572 0.406 104 327
## 564 Devin Robinson SF 23 WAS 7 0 95 19 32 0.594 0 2
## 565 Duncan Robinson PF 24 MIA 15 1 161 18 46 0.391 10 35
## 566 Glenn Robinson SF 25 DET 47 18 610 74 176 0.420 18 62
## 567 Jerome Robinson SG 21 LAC 33 0 320 44 110 0.400 18 57
## 568 Mitchell Robinson C 20 NYK 66 19 1360 202 291 0.694 0 0
## 569 Rajon Rondo PG 32 LAL 46 29 1369 175 432 0.405 51 142
## 570 Derrick Rose PG 30 MIN 51 13 1392 363 753 0.482 54 146
## 571 Terrence Ross SG 27 ORL 81 0 2150 440 1027 0.428 217 566
## 572 Terry Rozier PG 24 BOS 79 14 1791 258 666 0.387 119 337
## 573 Ricky Rubio PG 28 UTA 68 67 1899 295 730 0.404 79 254
## 574 D'Angelo Russell PG 22 BRK 81 81 2448 659 1517 0.434 234 635
## 575 Domantas Sabonis C 22 IND 74 5 1838 413 700 0.590 9 17
## 576 Brandon Sampson SG 21 CHI 14 2 214 28 60 0.467 11 29
## 577 JaKarr Sampson SF 25 CHI 4 0 127 29 54 0.537 5 14
## 578 Tomas Satoransky PG 27 WAS 80 54 2164 257 530 0.485 64 162
## 579 Dennis Schroder PG 25 OKC 79 14 2314 457 1104 0.414 124 364
## 580 Mike Scott PF 30 PHI 27 3 647 76 190 0.400 49 119
## 581 Mike Scott PF 30 LAC 52 0 748 92 230 0.400 52 133
## 582 Mike Scott PF 30 TOT 79 3 1395 168 420 0.400 101 252
## 583 Thabo Sefolosha SF 34 UTA 50 2 609 71 149 0.477 34 78
## 584 Wayne Selden SG 24 MEM 32 0 455 65 161 0.404 20 63
## 585 Wayne Selden SG 24 CHI 43 13 984 131 322 0.407 35 111
## 586 Wayne Selden SG 24 TOT 75 13 1439 196 483 0.406 55 174
## 587 Collin Sexton PG 20 CLE 82 72 2605 519 1206 0.430 119 296
## 588 Landry Shamet SG 21 LAC 25 23 694 87 210 0.414 68 151
## 589 Landry Shamet SG 21 PHI 54 4 1108 153 347 0.441 99 245
## 590 Landry Shamet SG 21 TOT 79 27 1802 240 557 0.431 167 396
## 591 Iman Shumpert SG 28 HOU 20 1 382 34 98 0.347 21 71
## 592 Iman Shumpert SG 28 SAC 42 40 1099 133 348 0.382 74 202
## 593 Iman Shumpert SG 28 TOT 62 41 1481 167 446 0.374 95 273
## 594 Pascal Siakam PF 24 TOR 80 79 2548 519 945 0.549 79 214
## 595 Jordan Sibert SG 26 ATL 1 0 4 1 1 1.000 1 1
## 596 Ben Simmons PG 22 PHI 79 79 2700 540 960 0.563 0 6
## 597 Jonathon Simmons SF 29 PHI 15 0 219 29 64 0.453 9 21
## 598 Jonathon Simmons SG 29 ORL 41 9 845 104 286 0.364 19 83
## 599 Jonathon Simmons SG-SF 29 TOT 56 9 1064 133 350 0.380 28 104
## 600 Kobi Simmons PG 21 CLE 1 0 2 0 0 NA 0 0
## 601 Anfernee Simons SG 19 POR 20 1 141 28 63 0.444 10 29
## 602 Marcus Smart SG 24 BOS 80 60 2200 239 567 0.422 126 346
## 603 Dennis Smith PG 21 NYK 21 18 600 121 293 0.413 24 83
## 604 Dennis Smith PG 21 DAL 32 32 908 157 357 0.440 43 125
## 605 Dennis Smith PG 21 TOT 53 50 1508 278 650 0.428 67 208
## 606 Ish Smith PG 30 DET 56 0 1251 205 489 0.419 44 135
## 607 JR Smith SG 33 CLE 11 4 222 27 79 0.342 12 39
## 608 Jason Smith C 32 NOP 2 0 20 2 9 0.222 2 7
## 609 Jason Smith PF 32 MIL 6 0 40 4 13 0.308 3 9
## 610 Jason Smith C 32 WAS 12 1 130 15 37 0.405 4 10
## 611 Jason Smith PF-C 32 TOT 20 1 190 21 59 0.356 9 26
## 612 Zhaire Smith SG 19 PHI 6 2 111 14 34 0.412 6 16
## 613 Tony Snell SF 27 MIL 74 12 1304 163 361 0.452 81 204
## 614 Ray Spalding PF 21 DAL 1 0 1 0 0 NA 0 0
## 615 Ray Spalding PF 21 TOT 14 3 148 25 47 0.532 0 3
## 616 Ray Spalding PF 21 PHO 13 3 147 25 47 0.532 0 3
## 617 Omari Spellman PF 21 ATL 46 11 805 98 244 0.402 44 128
## 618 Nik Stauskas SG 25 CLE 24 0 342 40 109 0.367 27 63
## 619 Nik Stauskas SG 25 POR 44 0 673 96 229 0.419 43 125
## 620 Nik Stauskas SG 25 TOT 68 0 1015 136 338 0.402 70 188
## 621 DJ Stephens SG 28 MEM 1 0 7 1 2 0.500 0 0
## 622 Lance Stephenson SG 28 LAL 68 3 1123 184 432 0.426 73 197
## 623 Edmond Sumner PG 23 IND 23 2 210 22 64 0.344 7 27
## 624 Caleb Swanigan PF 21 SAC 3 0 33 4 9 0.444 0 2
## 625 Caleb Swanigan PF 21 POR 18 0 145 14 44 0.318 1 5
## 626 Caleb Swanigan PF 21 TOT 21 0 178 18 53 0.340 1 7
## 627 Jayson Tatum SF 20 BOS 79 79 2455 466 1036 0.450 116 311
## 628 Jeff Teague PG 30 MIN 42 41 1264 176 416 0.423 35 105
## 629 Garrett Temple SG 32 LAC 26 6 510 42 106 0.396 16 54
## 630 Garrett Temple SG 32 MEM 49 49 1530 166 387 0.429 74 210
## 631 Garrett Temple SG 32 TOT 75 55 2040 208 493 0.422 90 264
## 632 Milos Teodosic PG 31 LAC 15 0 150 17 40 0.425 10 27
## 633 Jared Terrell SG 23 MIN 14 0 111 12 39 0.308 4 17
## 634 Emanuel Terry PF 22 MIA 1 0 3 0 1 0.000 0 0
## 635 Emanuel Terry PF 22 PHO 2 0 20 4 6 0.667 0 0
## 636 Emanuel Terry PF 22 TOT 3 0 23 4 7 0.571 0 0
## 637 Daniel Theis C 26 BOS 66 2 908 146 266 0.549 26 67
## 638 Isaiah Thomas SG 29 DEN 12 0 181 34 99 0.343 12 43
## 639 Khyri Thomas SG 22 DET 26 0 195 22 69 0.319 10 35
## 640 Lance Thomas PF 30 NYK 46 17 783 78 197 0.396 22 79
## 641 Klay Thompson SG 28 GSW 78 78 2652 655 1402 0.467 241 599
## 642 Tristan Thompson C 27 CLE 43 40 1198 201 380 0.529 0 0
## 643 Sindarius Thornwell SG 24 LAC 64 1 313 17 49 0.347 3 15
## 644 Anthony Tolliver PF 33 MIN 65 0 1079 99 259 0.382 81 215
## 645 Karl-Anthony Towns C 23 MIN 77 77 2545 681 1314 0.518 142 355
## 646 Gary Trent SG 20 POR 15 1 111 16 50 0.320 5 21
## 647 Allonzo Trier SG 23 NYK 64 3 1459 232 518 0.448 52 132
## 648 PJ Tucker PF 33 HOU 82 82 2802 207 523 0.396 146 387
## 649 Evan Turner PG 30 POR 73 2 1605 204 443 0.460 11 52
## 650 Myles Turner C 22 IND 74 74 2119 380 780 0.487 76 196
## 651 Ekpe Udoh C 31 UTA 51 1 320 50 72 0.694 0 0
## 652 Tyler Ulis PG 23 CHI 1 0 1 0 0 NA 0 0
## 653 Jonas Valanciunas C 26 MEM 19 17 527 152 279 0.545 5 18
## 654 Jonas Valanciunas C 26 TOR 30 10 564 149 259 0.575 9 30
## 655 Jonas Valanciunas C 26 TOT 49 27 1091 301 538 0.559 14 48
## 656 Jarred Vanderbilt PF 19 DEN 17 0 69 9 19 0.474 0 1
## 657 Fred VanVleet PG 24 TOR 64 28 1760 246 600 0.410 112 296
## 658 Noah Vonleh PF 23 NYK 68 57 1722 207 440 0.470 46 137
## 659 Nikola Vucevic C 28 ORL 80 80 2510 701 1354 0.518 84 231
## 660 Dwyane Wade SG 37 MIA 72 2 1885 416 960 0.433 86 261
## 661 Moritz Wagner C 21 LAL 43 5 446 71 171 0.415 22 77
## 662 Dion Waiters SG 27 MIA 44 28 1138 198 478 0.414 109 289
## 663 Kemba Walker PG 28 CHO 82 82 2863 731 1684 0.434 260 731
## 664 Lonnie Walker SG 20 SAS 17 0 118 16 46 0.348 5 13
## 665 John Wall PG 28 WAS 32 32 1104 245 552 0.444 51 169
## 666 Tyrone Wallace PG 24 LAC 62 0 628 92 217 0.424 4 19
## 667 Taurean Waller-Prince SF 24 ATL 55 47 1552 262 594 0.441 123 315
## 668 Brad Wanamaker PG 29 BOS 36 0 343 50 105 0.476 16 39
## 669 TJ Warren SF 25 PHO 43 36 1360 297 611 0.486 77 180
## 670 Julian Washburn SF 27 MEM 18 3 254 16 48 0.333 5 24
## 671 Yuta Watanabe SF 24 MEM 15 0 174 15 51 0.294 2 16
## 672 Thomas Welsh C 22 DEN 11 0 36 7 13 0.538 3 7
## 673 Russell Westbrook PG 30 OKC 73 73 2630 630 1473 0.428 119 411
## 674 Derrick White PG 24 SAS 67 55 1728 260 543 0.479 48 142
## 675 Okaro White PF 26 WAS 3 0 6 0 2 0.000 0 2
## 676 Hassan Whiteside C 29 MIA 72 53 1674 388 680 0.571 2 16
## 677 Andrew Wiggins SF 23 MIN 73 73 2543 498 1209 0.412 118 348
## 678 Alan Williams PF 26 BRK 5 0 26 8 13 0.615 0 1
## 679 CJ Williams SG 28 MIN 15 0 128 17 35 0.486 5 16
## 680 Johnathan Williams C 23 LAL 24 0 372 65 110 0.591 0 2
## 681 Kenrich Williams SF 24 NOP 46 29 1079 107 279 0.384 52 156
## 682 Lou Williams SG 32 LAC 75 1 1993 484 1138 0.425 105 291
## 683 Marvin Williams PF 32 CHO 75 75 2133 275 652 0.422 140 382
## 684 Robert Williams C 21 BOS 32 2 283 36 51 0.706 0 0
## 685 Troy Williams SF 24 SAC 21 0 312 44 98 0.449 14 44
## 686 DJ Wilson PF 22 MIL 48 3 882 104 251 0.414 46 127
## 687 Justise Winslow SF 22 MIA 66 52 1959 324 749 0.433 96 256
## 688 Christian Wood PF 23 MIL 13 0 62 12 25 0.480 3 5
## 689 Christian Wood PF 23 NOP 8 2 189 49 92 0.533 6 21
## 690 Christian Wood PF 23 TOT 21 2 251 61 117 0.521 9 26
## 691 Delon Wright PG 26 MEM 26 11 802 115 265 0.434 20 78
## 692 Delon Wright PG 26 TOR 49 2 897 127 293 0.433 30 90
## 693 Delon Wright PG 26 TOT 75 13 1699 242 558 0.434 50 168
## 694 Guerschon Yabusele PF 23 BOS 41 1 251 35 77 0.455 9 28
## 695 Nick Young SG 33 DEN 4 0 37 3 9 0.333 3 8
## 696 Thaddeus Young PF 30 IND 81 81 2489 443 841 0.527 51 146
## 697 Trae Young PG 20 ATL 81 81 2503 525 1256 0.418 156 482
## 698 Cody Zeller C 26 CHO 49 47 1243 190 345 0.551 6 22
## 699 Tyler Zeller C 29 ATL 2 0 11 0 2 0.000 0 1
## 700 Tyler Zeller C 29 TOT 6 1 93 16 30 0.533 0 1
## 701 Tyler Zeller C 29 MEM 4 1 82 16 28 0.571 0 0
## 702 Ivica Zubac C 21 LAC 26 25 524 100 186 0.538 0 0
## 703 Ivica Zubac C 21 LAL 33 12 516 112 193 0.580 0 0
## 704 Ivica Zubac C 21 TOT 59 37 1040 212 379 0.559 0 0
## 705 Dario Saric PF 24 PHI 13 13 396 48 132 0.364 21 70
## 706 Dario Saric PF 24 MIN 68 28 1627 256 564 0.454 97 253
## 707 Dario Saric PF 24 TOT 81 41 2023 304 696 0.437 118 323
## 708 Ante Zizic C 22 CLE 59 25 1082 183 331 0.553 0 0
## X3P. X2P X2PA X2P. eFG. FT FTA FT. ORB DRB TRB AST STL BLK TOV PF
## 1 0.323 15 30 0.500 0.487 12 13 0.923 5 43 48 20 17 6 14 53
## 2 0.133 2 3 0.667 0.278 7 10 0.700 3 22 25 8 1 4 4 24
## 3 0.338 13 36 0.361 0.459 7 9 0.778 11 49 60 65 14 5 28 45
## 4 0.000 481 807 0.596 0.595 146 292 0.500 391 369 760 124 117 76 135 204
## 5 0.200 277 471 0.588 0.579 166 226 0.735 165 432 597 184 71 65 121 203
## 6 0.261 5 13 0.385 0.389 4 4 1.000 3 16 19 5 1 4 6 13
## 7 0.000 3 6 0.500 0.300 1 2 0.500 1 3 4 6 2 0 2 4
## 8 0.238 674 1277 0.528 0.522 349 412 0.847 251 493 744 194 43 107 144 179
## 9 0.250 10 27 0.370 0.372 8 12 0.667 11 15 26 13 1 0 8 7
## 10 0.323 35 79 0.443 0.466 45 60 0.750 3 20 23 25 6 6 33 47
## 11 0.133 329 523 0.629 0.595 197 278 0.709 191 481 672 110 43 120 103 184
## 12 0.472 48 105 0.457 0.521 42 54 0.778 8 43 51 76 16 4 26 46
## 13 0.343 161 313 0.514 0.514 150 173 0.867 112 498 610 104 68 33 72 143
## 14 0.312 40 80 0.500 0.484 26 35 0.743 24 60 84 23 22 13 23 48
## 15 0.265 141 242 0.583 0.560 37 64 0.578 48 203 251 128 54 37 58 112
## 16 0.333 0 3 0.000 0.333 1 2 0.500 4 5 9 2 1 0 2 2
## 17 0.206 12 26 0.462 0.375 11 14 0.786 14 31 45 17 3 1 12 23
## 18 0.225 12 29 0.414 0.370 12 16 0.750 18 36 54 19 4 1 14 25
## 19 NA 0 3 0.000 0.000 0 0 NA 1 2 3 1 0 1 1 0
## 20 0.256 669 1044 0.641 0.599 500 686 0.729 159 739 898 424 92 110 268 232
## 21 NA 0 3 0.000 0.000 2 4 0.500 0 1 1 0 2 0 1 0
## 22 0.328 28 57 0.491 0.492 15 22 0.682 9 45 54 5 4 7 8 32
## 23 0.332 116 202 0.574 0.536 36 62 0.581 58 139 197 47 46 22 55 140
## 24 0.373 106 201 0.527 0.544 89 102 0.873 27 192 219 269 65 4 63 171
## 25 0.360 36 88 0.409 0.489 36 43 0.837 16 129 145 87 38 8 39 44
## 26 0.322 113 214 0.528 0.502 94 121 0.777 34 192 226 165 53 13 67 86
## 27 0.334 149 302 0.493 0.498 130 164 0.793 50 321 371 252 91 21 106 130
## 28 0.421 187 366 0.511 0.566 181 209 0.866 41 162 203 426 52 4 128 115
## 29 0.000 509 866 0.588 0.585 141 189 0.746 223 506 729 125 61 67 126 209
## 30 0.437 84 170 0.494 0.549 34 46 0.739 8 81 89 47 12 5 18 72
## 31 0.313 326 610 0.534 0.525 181 262 0.691 162 309 471 62 33 59 98 120
## 32 0.000 0 0 NA 0.000 0 0 NA 0 4 4 2 1 1 2 2
## 33 0.077 3 7 0.429 0.225 5 6 0.833 1 10 11 15 6 1 5 18
## 34 0.111 3 7 0.429 0.281 5 6 0.833 1 6 7 13 5 0 3 16
## 35 0.222 8 24 0.333 0.333 8 11 0.727 2 13 15 12 1 2 14 11
## 36 0.329 110 228 0.482 0.488 20 48 0.417 54 197 251 255 69 19 103 114
## 37 0.300 96 173 0.555 0.525 37 63 0.587 64 169 233 39 13 64 43 102
## 38 0.297 123 257 0.479 0.468 55 78 0.705 13 82 95 211 22 1 72 50
## 39 0.408 88 180 0.489 0.540 64 80 0.800 21 133 154 53 17 2 30 43
## 40 0.389 169 406 0.416 0.489 165 198 0.833 36 171 207 62 33 11 68 79
## 41 0.395 257 586 0.439 0.504 229 278 0.824 57 304 361 115 50 13 98 122
## 42 0.342 118 264 0.447 0.475 57 74 0.770 32 167 199 124 18 22 65 82
## 43 0.250 47 90 0.522 0.468 18 28 0.643 16 67 83 17 18 14 14 29
## 44 0.389 137 264 0.519 0.553 77 89 0.865 71 319 390 247 71 43 117 140
## 45 0.296 53 132 0.402 0.420 16 28 0.571 11 51 62 119 18 2 32 56
## 46 0.344 84 162 0.519 0.518 53 62 0.855 88 152 240 57 12 34 40 125
## 47 0.320 182 391 0.465 0.472 127 175 0.726 37 224 261 152 89 42 121 170
## 48 0.351 555 1013 0.548 0.540 362 448 0.808 89 322 411 448 121 58 224 226
## 49 0.402 186 332 0.560 0.584 56 66 0.848 35 165 200 97 55 10 55 116
## 50 0.176 72 136 0.529 0.500 28 39 0.718 13 47 60 25 9 10 27 42
## 51 0.372 138 295 0.468 0.520 112 124 0.903 16 182 198 132 35 8 72 121
## 52 0.000 99 190 0.521 0.516 25 41 0.610 55 129 184 76 20 51 42 80
## 53 0.289 225 443 0.508 0.487 87 136 0.640 54 304 358 202 105 41 142 190
## 54 0.218 66 96 0.688 0.503 32 54 0.593 34 149 183 56 18 22 37 90
## 55 0.294 2 13 0.154 0.362 0 0 NA 2 7 9 10 1 0 2 7
## 56 0.429 59 115 0.513 0.610 53 60 0.883 23 241 264 100 35 33 43 133
## 57 0.397 82 195 0.421 0.524 96 123 0.780 76 312 388 300 67 43 85 265
## 58 0.000 91 150 0.607 0.603 58 83 0.699 79 111 190 38 18 29 20 72
## 59 NA 89 156 0.571 0.571 58 91 0.637 81 166 247 33 11 41 34 103
## 60 0.401 181 336 0.539 0.566 70 92 0.761 125 319 444 147 54 56 82 197
## 61 0.396 130 305 0.426 0.465 50 76 0.658 7 99 106 42 12 9 35 41
## 62 0.329 346 594 0.582 0.548 177 236 0.750 82 280 362 430 116 29 165 156
## 63 0.256 37 67 0.552 0.491 10 13 0.769 26 72 98 13 7 8 11 20
## 64 0.360 227 491 0.462 0.496 134 162 0.827 40 203 243 267 72 15 117 142
## 65 0.425 358 665 0.538 0.575 246 305 0.807 33 300 333 161 69 1 134 138
## 66 NA 18 36 0.500 0.500 3 3 1.000 12 43 55 11 3 8 8 22
## 67 0.354 46 66 0.697 0.599 13 27 0.481 47 118 165 40 17 39 36 99
## 68 0.000 5 25 0.200 0.152 9 15 0.600 9 16 25 15 9 4 6 9
## 69 0.326 451 841 0.536 0.521 393 454 0.866 39 226 265 433 56 13 264 200
## 70 0.324 22 39 0.564 0.526 13 15 0.867 16 40 56 2 6 24 7 31
## 71 0.384 59 115 0.513 0.537 23 25 0.920 8 36 44 56 14 0 28 34
## 72 0.337 103 248 0.415 0.452 20 25 0.800 35 96 131 96 27 16 61 133
## 73 0.351 162 363 0.446 0.479 43 50 0.860 43 132 175 152 41 16 89 167
## 74 NA 8 16 0.500 0.500 1 2 0.500 9 6 15 1 2 2 3 6
## 75 0.286 16 35 0.457 0.449 9 13 0.692 4 13 17 10 12 2 8 16
## 76 0.333 23 44 0.523 0.514 22 30 0.733 22 37 59 29 20 5 11 47
## 77 0.318 39 79 0.494 0.488 31 43 0.721 26 50 76 39 32 7 19 63
## 78 0.335 137 250 0.548 0.523 95 118 0.805 56 208 264 173 129 38 70 201
## 79 0.325 172 311 0.553 0.527 58 77 0.753 67 256 323 95 55 49 50 111
## 80 0.324 44 104 0.423 0.438 15 26 0.577 5 69 74 87 11 2 31 66
## 81 0.409 19 33 0.576 0.603 15 19 0.789 8 55 63 22 6 4 16 35
## 82 0.426 274 504 0.544 0.575 141 152 0.928 65 223 288 205 46 13 91 102
## 83 0.375 34 82 0.415 0.463 22 30 0.733 9 22 31 16 10 4 19 50
## 84 0.278 61 115 0.530 0.494 23 33 0.697 12 33 45 25 9 4 21 33
## 85 0.258 101 221 0.457 0.436 45 60 0.750 48 137 185 91 40 36 46 178
## 86 0.344 273 516 0.529 0.525 133 202 0.658 65 248 313 100 69 32 99 186
## 87 0.214 17 43 0.395 0.366 3 3 1.000 5 26 31 28 12 5 16 22
## 88 0.361 92 165 0.558 0.550 29 42 0.690 29 155 184 84 25 8 46 88
## 89 0.319 75 165 0.455 0.462 32 47 0.681 35 110 145 80 21 5 30 56
## 90 0.348 201 384 0.523 0.523 87 120 0.725 25 144 169 230 37 4 88 127
## 91 0.333 276 403 0.685 0.648 107 137 0.781 113 341 454 92 25 67 60 126
## 92 0.343 29 54 0.537 0.523 17 21 0.810 2 48 50 20 16 7 11 30
## 93 0.388 68 147 0.463 0.542 56 64 0.875 20 103 123 109 24 5 54 79
## 94 0.377 97 201 0.483 0.537 73 85 0.859 22 151 173 129 40 12 65 109
## 95 0.356 62 117 0.530 0.532 41 49 0.837 13 24 37 65 12 2 20 25
## 96 0.349 118 272 0.434 0.455 62 75 0.827 15 47 62 94 21 5 29 33
## 97 0.352 180 389 0.463 0.482 103 124 0.831 28 71 99 159 33 7 49 58
## 98 0.000 9 14 0.643 0.450 4 5 0.800 2 20 22 10 8 1 4 7
## 99 0.372 31 71 0.437 0.482 33 38 0.868 2 25 27 20 6 4 15 22
## 100 0.378 91 221 0.412 0.466 79 98 0.806 26 160 186 98 25 16 46 62
## 101 0.363 131 306 0.428 0.469 116 141 0.823 30 205 235 128 39 21 65 91
## 102 0.296 25 55 0.455 0.451 8 12 0.667 4 24 28 9 6 8 9 31
## 103 0.378 57 112 0.509 0.525 48 61 0.787 16 36 52 43 24 10 14 18
## 104 0.338 294 599 0.491 0.494 264 304 0.868 105 185 290 220 99 29 81 93
## 105 0.347 351 711 0.494 0.499 312 365 0.855 121 221 342 263 123 39 95 111
## 106 0.369 48 95 0.505 0.533 42 50 0.840 42 116 158 50 14 33 38 81
## 107 0.246 31 63 0.492 0.433 9 11 0.818 11 49 60 115 16 3 35 64
## 108 0.347 174 321 0.542 0.530 137 158 0.867 48 190 238 110 73 13 65 137
## 109 0.400 0 1 0.000 0.500 0 0 NA 1 3 4 3 0 1 2 2
## 110 0.368 4 10 0.400 0.500 4 4 1.000 0 5 5 19 2 1 4 4
## 111 0.347 26 57 0.456 0.492 15 20 0.750 5 44 49 62 12 0 29 46
## 112 0.354 30 68 0.441 0.494 19 24 0.792 6 52 58 84 14 2 35 52
## 113 NA 474 732 0.648 0.648 166 261 0.636 298 550 848 96 44 102 94 168
## 114 0.342 121 265 0.457 0.487 184 242 0.760 68 281 349 85 31 10 73 114
## 115 0.333 22 83 0.265 0.395 26 32 0.813 14 52 66 69 26 11 33 55
## 116 0.389 73 152 0.480 0.550 47 66 0.712 31 163 194 87 44 27 48 141
## 117 0.188 174 339 0.513 0.493 89 112 0.795 87 220 307 78 26 58 65 152
## 118 0.158 18 43 0.419 0.363 20 27 0.741 16 41 57 49 11 9 10 21
## 119 0.368 18 42 0.429 0.467 12 26 0.462 3 10 13 21 9 6 10 27
## 120 0.263 36 85 0.424 0.415 32 53 0.604 19 51 70 70 20 15 20 48
## 121 0.480 53 123 0.431 0.514 51 64 0.797 20 47 67 77 24 9 42 54
## 122 0.349 71 118 0.602 0.581 39 58 0.672 17 98 115 26 20 9 23 35
## 123 0.500 411 739 0.556 0.557 140 254 0.551 181 497 678 194 96 51 84 227
## 124 0.667 2 5 0.400 0.625 0 0 NA 1 2 3 4 1 0 0 0
## 125 0.200 2 5 0.400 0.350 2 2 1.000 3 5 8 1 0 0 1 3
## 126 NA 8 12 0.667 0.667 10 18 0.556 7 32 39 6 2 1 7 21
## 127 0.000 53 86 0.616 0.609 41 69 0.594 85 183 268 31 19 22 35 89
## 128 0.000 61 98 0.622 0.616 51 87 0.586 92 215 307 37 21 23 42 110
## 129 0.325 10 26 0.385 0.447 5 7 0.714 4 43 47 10 3 3 7 29
## 130 0.390 45 89 0.506 0.551 13 18 0.722 44 124 168 72 22 18 39 94
## 131 0.373 55 115 0.478 0.526 18 25 0.720 48 167 215 82 25 21 46 123
## 132 NA 1 3 0.333 0.333 0 0 NA 0 0 0 1 0 0 0 1
## 133 0.400 0 3 0.000 0.375 0 0 NA 1 3 4 4 1 1 1 2
## 134 0.067 10 19 0.526 0.338 6 7 0.857 7 21 28 6 2 4 12 17
## 135 0.263 41 89 0.461 0.435 26 38 0.684 33 81 114 16 15 7 24 64
## 136 0.222 51 108 0.472 0.417 32 45 0.711 40 102 142 22 17 11 36 81
## 137 0.297 9 13 0.692 0.467 7 7 1.000 24 92 116 18 20 26 7 47
## 138 0.327 85 181 0.470 0.480 33 37 0.892 13 76 89 94 22 8 58 95
## 139 0.324 385 735 0.524 0.509 162 192 0.844 82 188 270 196 57 13 135 112
## 140 0.348 410 673 0.609 0.593 203 266 0.763 219 376 595 121 22 39 120 199
## 141 0.331 149 279 0.534 0.523 94 126 0.746 109 215 324 71 25 66 77 174
## 142 0.407 229 465 0.492 0.527 158 190 0.832 36 196 232 459 110 9 125 138
## 143 0.238 8 18 0.444 0.397 8 9 0.889 8 22 30 3 5 1 3 3
## 144 0.364 335 694 0.483 0.507 343 406 0.845 40 199 239 449 94 22 130 123
## 145 0.330 97 150 0.647 0.560 29 40 0.725 61 197 258 122 33 25 33 81
## 146 0.405 123 239 0.515 0.557 20 26 0.769 22 135 157 116 20 3 50 92
## 147 0.274 152 276 0.551 0.515 106 144 0.736 43 204 247 107 40 44 72 109
## 148 0.390 20 40 0.500 0.556 17 23 0.739 7 60 67 14 24 23 22 45
## 149 0.372 51 97 0.526 0.545 51 66 0.773 21 105 126 32 50 24 25 81
## 150 0.378 71 137 0.518 0.548 68 89 0.764 28 165 193 46 74 47 47 126
## 151 0.378 39 114 0.342 0.499 41 56 0.732 16 132 148 46 23 13 46 102
## 152 0.324 99 174 0.569 0.526 49 70 0.700 89 174 263 72 37 46 44 175
## 153 0.332 107 236 0.453 0.474 93 110 0.845 8 77 85 229 33 12 99 75
## 154 0.000 3 5 0.600 0.500 0 0 NA 1 1 2 1 1 0 1 0
## 155 0.000 5 9 0.556 0.500 5 7 0.714 5 5 10 5 1 0 0 3
## 156 0.000 8 14 0.571 0.500 5 7 0.714 6 6 12 6 2 0 1 3
## 157 0.331 145 275 0.527 0.508 142 197 0.721 60 324 384 133 64 31 85 170
## 158 0.462 45 93 0.484 0.570 14 18 0.778 48 140 188 50 27 13 22 71
## 159 0.450 99 214 0.463 0.577 44 52 0.846 27 93 120 66 36 12 61 97
## 160 0.437 278 530 0.525 0.604 263 287 0.916 45 324 369 361 92 25 192 166
## 161 0.381 39 81 0.481 0.545 18 23 0.783 13 60 73 26 26 5 27 79
## 162 0.331 482 881 0.547 0.540 344 433 0.794 174 498 672 218 88 135 112 132
## 163 0.000 15 21 0.714 0.682 6 10 0.600 10 26 36 5 3 5 3 12
## 164 0.000 186 300 0.620 0.616 100 162 0.617 216 478 694 61 35 33 64 226
## 165 NA 0 1 0.000 0.000 0 0 NA 1 0 1 0 0 0 0 0
## 166 0.382 176 309 0.570 0.571 92 113 0.814 105 375 480 90 69 71 84 214
## 167 0.385 17 35 0.486 0.510 8 10 0.800 9 24 33 9 11 0 5 13
## 168 0.286 84 159 0.528 0.505 20 36 0.556 44 71 115 37 27 7 19 34
## 169 0.306 101 194 0.521 0.506 28 46 0.609 53 95 148 46 38 7 24 47
## 170 NA 1 5 0.200 0.200 1 2 0.500 2 2 4 0 1 0 0 2
## 171 0.364 2 8 0.250 0.421 4 4 1.000 0 10 10 29 2 0 11 9
## 172 0.336 52 104 0.500 0.502 38 48 0.792 6 61 67 152 12 2 57 66
## 173 0.338 54 112 0.482 0.496 42 52 0.808 6 71 77 181 14 2 68 75
## 174 0.318 45 74 0.608 0.559 25 35 0.714 20 53 73 18 15 8 14 24
## 175 0.156 624 1268 0.492 0.483 366 441 0.830 54 408 462 475 86 36 199 177
## 176 0.500 6 13 0.462 0.636 4 5 0.800 8 5 13 1 0 1 3 9
## 177 0.250 167 267 0.625 0.622 50 67 0.746 75 257 332 33 29 33 49 113
## 178 0.167 71 141 0.504 0.467 36 59 0.610 38 59 97 17 21 10 23 77
## 179 0.339 170 321 0.530 0.527 88 106 0.830 81 230 311 72 48 41 57 134
## 180 0.335 242 458 0.528 0.517 287 356 0.806 26 140 166 311 40 17 152 187
## 181 0.265 28 41 0.683 0.492 9 12 0.750 16 49 65 31 13 6 19 38
## 182 0.327 338 672 0.503 0.497 346 485 0.713 86 477 563 429 77 25 247 137
## 183 0.256 22 50 0.440 0.416 16 26 0.615 9 34 43 17 7 1 10 20
## 184 0.366 41 82 0.500 0.526 22 35 0.629 18 52 70 39 7 1 17 33
## 185 0.333 63 132 0.477 0.489 38 61 0.623 27 86 113 56 14 2 27 53
## 186 0.368 164 356 0.461 0.506 73 98 0.745 34 228 262 135 58 10 71 135
## 187 0.250 6 13 0.462 0.429 1 2 0.500 6 11 17 5 2 0 0 2
## 188 0.348 122 269 0.454 0.479 79 101 0.782 20 91 111 174 30 5 71 81
## 189 0.132 556 1014 0.548 0.536 243 412 0.590 423 809 1232 112 136 138 175 272
## 190 0.351 48 88 0.545 0.533 32 46 0.696 34 121 155 83 36 16 43 131
## 191 0.354 181 410 0.441 0.458 55 69 0.797 19 168 187 277 68 21 104 166
## 192 0.353 584 995 0.587 0.571 448 506 0.885 33 464 497 457 58 84 225 155
## 193 1.000 1 2 0.500 0.833 0 0 NA 0 1 1 2 0 0 0 0
## 194 0.250 0 0 NA 0.375 0 0 NA 1 1 2 0 0 0 0 0
## 195 0.500 2 6 0.333 0.500 2 2 1.000 0 9 9 1 0 0 0 2
## 196 0.441 20 51 0.392 0.500 17 23 0.739 5 52 57 15 7 2 9 25
## 197 0.447 22 57 0.386 0.500 19 25 0.760 5 61 66 16 7 2 9 27
## 198 0.368 12 29 0.414 0.530 14 16 0.875 6 41 47 29 24 3 14 40
## 199 0.373 34 56 0.607 0.570 25 33 0.758 8 52 60 43 30 3 26 52
## 200 0.371 46 85 0.541 0.554 39 49 0.796 14 93 107 72 54 6 40 92
## 201 0.300 501 936 0.535 0.517 522 649 0.804 160 711 871 234 46 122 226 211
## 202 0.306 23 47 0.489 0.476 16 23 0.696 23 42 65 14 3 7 11 39
## 203 0.367 60 91 0.659 0.597 42 58 0.724 37 80 117 27 38 16 23 111
## 204 0.353 83 138 0.601 0.563 58 81 0.716 60 122 182 41 41 23 34 150
## 205 NA 15 26 0.577 0.577 11 13 0.846 6 28 34 7 2 5 8 11
## 206 0.267 14 38 0.368 0.377 0 1 0.000 6 19 25 23 5 3 11 28
## 207 0.000 0 0 NA 0.000 0 0 NA 0 0 0 0 0 0 0 0
## 208 0.000 3 11 0.273 0.214 0 0 NA 1 11 12 10 3 0 6 8
## 209 0.000 3 11 0.273 0.231 0 0 NA 1 11 12 10 3 0 6 8
## 210 0.356 180 444 0.405 0.448 115 160 0.719 33 168 201 166 58 18 118 117
## 211 0.290 83 179 0.464 0.456 68 86 0.791 16 52 68 110 14 5 52 69
## 212 0.200 24 37 0.649 0.607 10 16 0.625 15 29 44 2 2 4 6 8
## 213 0.350 124 203 0.611 0.603 54 83 0.651 82 124 206 18 15 19 27 74
## 214 0.320 148 240 0.617 0.604 64 99 0.646 97 153 250 20 17 23 33 82
## 215 0.218 346 541 0.640 0.600 154 228 0.675 207 353 560 89 56 106 84 163
## 216 0.328 35 74 0.473 0.481 12 13 0.923 4 30 34 52 10 6 14 29
## 217 0.000 95 175 0.543 0.531 50 73 0.685 79 139 218 37 11 7 33 69
## 218 0.366 79 141 0.560 0.552 37 51 0.725 33 108 141 72 40 16 47 231
## 219 0.362 99 203 0.488 0.511 60 67 0.896 13 96 109 137 36 4 40 64
## 220 0.311 149 274 0.544 0.507 73 103 0.709 138 251 389 95 69 36 74 186
## 221 0.426 185 378 0.489 0.568 69 78 0.885 18 221 239 175 45 4 80 159
## 222 0.340 315 619 0.509 0.509 137 170 0.806 38 220 258 295 71 12 154 225
## 223 0.371 419 870 0.482 0.497 303 417 0.727 43 261 304 590 133 45 227 204
## 224 0.000 7 15 0.467 0.333 1 4 0.250 3 2 5 1 1 0 1 6
## 225 0.417 18 42 0.429 0.500 9 13 0.692 9 22 31 42 5 1 16 19
## 226 0.351 61 118 0.517 0.521 32 41 0.780 32 105 137 206 25 4 60 93
## 227 0.366 79 160 0.494 0.515 41 54 0.759 41 127 168 248 30 5 76 112
## 228 0.000 8 16 0.500 0.276 6 6 1.000 1 6 7 8 3 0 5 5
## 229 0.405 11 38 0.289 0.504 11 14 0.786 4 48 52 20 6 5 13 44
## 230 0.286 61 141 0.433 0.432 21 37 0.568 26 44 70 59 17 5 25 52
## 231 0.433 248 512 0.484 0.554 367 406 0.904 54 363 417 178 49 23 99 129
## 232 0.355 93 207 0.449 0.503 81 96 0.844 49 122 171 85 37 8 24 135
## 233 0.000 11 19 0.579 0.407 4 4 1.000 0 3 3 7 1 1 2 3
## 234 0.442 64 135 0.474 0.527 40 52 0.769 24 148 172 101 24 23 36 70
## 235 0.344 227 462 0.491 0.499 152 201 0.756 56 399 455 248 60 63 119 147
## 236 0.363 291 597 0.487 0.505 192 253 0.759 80 547 627 349 84 86 155 217
## 237 0.333 0 3 0.000 0.250 1 2 0.500 0 10 10 2 0 1 2 1
## 238 0.500 36 78 0.462 0.494 27 38 0.711 22 105 127 50 5 14 14 28
## 239 0.462 36 81 0.444 0.479 28 40 0.700 22 115 137 52 5 15 16 29
## 240 0.402 302 562 0.537 0.554 120 147 0.816 63 407 470 182 54 34 114 159
## 241 0.386 415 857 0.484 0.529 453 540 0.839 105 523 628 318 170 34 205 214
## 242 0.324 293 503 0.583 0.576 134 177 0.757 172 286 458 84 53 39 73 186
## 243 0.000 175 342 0.512 0.503 58 91 0.637 66 156 222 85 31 22 73 150
## 244 0.367 290 577 0.503 0.512 156 195 0.800 57 175 232 270 96 45 141 175
## 245 NA 476 712 0.669 0.669 332 522 0.636 309 732 1041 161 66 187 130 231
## 246 0.333 4 17 0.235 0.304 9 11 0.818 1 2 3 14 0 0 3 7
## 247 0.349 349 699 0.499 0.507 185 253 0.731 129 445 574 289 57 56 162 172
## 248 0.360 168 338 0.497 0.525 119 152 0.783 17 131 148 129 41 27 90 143
## 249 NA 99 186 0.532 0.532 35 48 0.729 67 194 261 65 6 24 50 92
## 250 0.281 40 95 0.421 0.421 35 46 0.761 10 53 63 121 23 2 30 48
## 251 0.297 26 63 0.413 0.435 18 22 0.818 23 84 107 34 13 7 17 68
## 252 0.392 294 530 0.555 0.567 157 221 0.710 96 321 417 79 61 100 67 214
## 253 0.364 52 110 0.473 0.509 26 40 0.650 19 79 98 156 44 6 51 78
## 254 0.000 0 0 NA 0.000 0 0 NA 0 0 0 0 0 0 0 0
## 255 0.455 95 195 0.487 0.622 37 44 0.841 60 257 317 126 73 53 75 171
## 256 0.285 141 257 0.549 0.501 63 91 0.692 60 421 481 454 95 70 169 197
## 257 0.354 75 137 0.547 0.535 57 68 0.838 30 152 182 40 33 27 55 126
## 258 0.413 46 84 0.548 0.582 17 21 0.810 32 125 157 14 12 8 23 70
## 259 0.396 113 216 0.523 0.545 63 80 0.788 72 180 252 36 33 26 64 123
## 260 0.403 159 300 0.530 0.558 80 101 0.792 104 305 409 50 45 34 87 193
## 261 0.347 215 367 0.586 0.555 183 206 0.888 57 252 309 137 43 39 101 160
## 262 0.362 430 819 0.525 0.532 414 550 0.753 100 465 565 402 52 28 253 199
## 263 0.348 15 37 0.405 0.450 3 6 0.500 10 37 47 22 6 1 16 19
## 264 0.000 3 7 0.429 0.250 2 2 1.000 0 1 1 5 1 0 1 1
## 265 0.321 63 127 0.496 0.489 33 43 0.767 7 54 61 37 12 2 24 35
## 266 0.347 165 389 0.424 0.469 199 233 0.854 26 135 161 122 42 6 81 106
## 267 0.340 228 516 0.442 0.474 232 276 0.841 33 189 222 159 54 8 105 141
## 268 0.368 465 881 0.528 0.541 754 858 0.879 66 452 518 586 158 58 387 244
## 269 0.275 156 268 0.582 0.530 49 73 0.671 77 192 269 74 67 53 45 163
## 270 0.176 543 871 0.623 0.617 266 414 0.643 184 351 535 162 71 110 132 255
## 271 0.310 70 147 0.476 0.470 102 134 0.761 12 100 112 122 35 16 56 133
## 272 0.339 188 395 0.476 0.488 115 144 0.799 41 119 160 127 55 19 68 113
## 273 0.474 191 362 0.528 0.622 110 133 0.827 52 239 291 181 38 17 121 182
## 274 0.326 143 264 0.542 0.524 74 88 0.841 32 181 213 79 11 13 42 61
## 275 0.434 312 597 0.523 0.561 192 219 0.877 37 395 432 150 40 24 109 123
## 276 0.397 455 861 0.528 0.549 266 307 0.866 69 576 645 229 51 37 151 184
## 277 0.000 1 1 1.000 0.500 0 0 NA 0 0 0 0 0 0 0 1
## 278 0.200 1 2 0.500 0.333 1 2 0.500 2 3 5 7 0 0 2 7
## 279 0.214 9 25 0.360 0.346 16 16 1.000 4 11 15 17 4 2 10 26
## 280 0.200 11 28 0.393 0.349 17 18 0.944 6 14 20 24 4 2 12 34
## 281 0.270 160 337 0.475 0.460 82 123 0.667 33 189 222 139 89 30 60 124
## 282 0.336 97 190 0.511 0.506 55 80 0.688 35 213 248 93 64 40 58 147
## 283 0.333 18 35 0.514 0.512 11 14 0.786 21 26 47 15 7 12 13 56
## 284 0.000 11 21 0.524 0.333 3 4 0.750 3 24 27 2 0 0 3 9
## 285 0.333 219 404 0.542 0.527 156 187 0.834 51 271 322 244 62 23 105 104
## 286 0.355 20 36 0.556 0.545 6 10 0.600 16 55 71 14 7 11 12 16
## 287 0.365 72 133 0.541 0.545 66 86 0.767 64 201 265 55 27 24 37 94
## 288 0.385 138 256 0.539 0.544 100 144 0.694 117 194 311 60 16 20 58 98
## 289 0.276 149 312 0.478 0.457 87 114 0.763 28 211 239 88 57 8 88 110
## 290 NA 4 8 0.500 0.500 4 5 0.800 2 5 7 2 1 3 1 5
## 291 0.427 345 709 0.487 0.560 171 193 0.886 106 306 412 205 58 33 146 202
## 292 0.200 3 5 0.600 0.450 0 2 0.000 0 5 5 2 1 0 1 1
## 293 0.464 42 79 0.532 0.575 17 20 0.850 12 15 27 36 12 1 20 35
## 294 0.280 80 144 0.556 0.493 53 65 0.815 27 94 121 99 40 7 31 67
## 295 0.314 122 223 0.547 0.516 70 85 0.824 39 109 148 135 52 8 51 102
## 296 0.317 36 77 0.468 0.472 23 32 0.719 34 99 133 55 23 10 31 80
## 297 0.000 60 113 0.531 0.517 31 47 0.660 34 89 123 26 18 15 11 87
## 298 0.339 62 135 0.459 0.483 41 50 0.820 5 62 67 87 21 13 40 71
## 299 0.325 429 796 0.539 0.523 208 271 0.768 75 259 334 518 109 54 210 148
## 300 0.333 84 188 0.447 0.474 54 60 0.900 27 127 154 61 54 15 57 85
## 301 0.359 54 124 0.435 0.506 41 46 0.891 19 150 169 85 67 21 47 79
## 302 0.348 138 312 0.442 0.490 95 106 0.896 46 277 323 146 121 36 104 164
## 303 NA 0 0 NA NA 0 0 NA 0 0 0 0 0 0 0 0
## 304 0.184 191 438 0.436 0.420 118 183 0.645 83 227 310 96 44 27 68 107
## 305 NA 222 365 0.608 0.608 128 175 0.731 115 216 331 60 42 79 52 194
## 306 0.345 69 133 0.519 0.518 33 41 0.805 7 38 45 34 21 7 19 45
## 307 0.362 139 302 0.460 0.488 104 114 0.912 18 94 112 92 38 5 36 101
## 308 0.356 208 435 0.478 0.498 137 155 0.884 25 132 157 126 59 12 55 146
## 309 0.360 314 520 0.604 0.586 78 95 0.821 120 338 458 283 59 86 102 126
## 310 0.416 44 74 0.595 0.615 56 71 0.789 25 115 140 40 21 11 35 80
## 311 NA 43 69 0.623 0.623 29 48 0.604 24 59 83 4 7 4 16 34
## 312 0.385 139 304 0.457 0.522 41 56 0.732 60 185 245 214 65 25 109 155
## 313 0.273 3 10 0.300 0.357 0 0 NA 4 7 11 0 1 0 0 7
## 314 0.400 2 3 0.667 0.615 1 2 0.500 1 2 3 3 1 0 0 3
## 315 0.280 82 159 0.516 0.493 23 38 0.605 31 154 185 34 23 6 25 59
## 316 0.290 415 708 0.586 0.557 135 177 0.763 156 445 601 99 29 103 114 211
## 317 0.333 103 158 0.652 0.579 39 67 0.582 48 204 252 216 61 51 52 95
## 318 0.391 170 319 0.533 0.565 87 123 0.707 35 295 330 469 98 20 193 180
## 319 0.000 0 3 0.000 0.000 0 0 NA 1 1 2 0 1 0 1 0
## 320 0.330 331 635 0.521 0.518 195 289 0.675 41 226 267 154 28 31 129 149
## 321 0.401 430 807 0.533 0.557 214 245 0.873 71 264 335 464 103 34 172 167
## 322 0.323 176 345 0.510 0.499 110 135 0.815 99 312 411 80 59 98 75 143
## 323 0.367 84 195 0.431 0.465 84 103 0.816 37 147 184 73 28 22 44 123
## 324 0.363 109 221 0.493 0.514 61 74 0.824 94 208 302 52 32 20 48 172
## 325 0.333 6 9 0.667 0.600 4 4 1.000 2 1 3 5 2 0 1 4
## 326 0.314 141 278 0.507 0.493 54 73 0.740 25 109 134 69 25 2 48 92
## 327 0.359 247 447 0.553 0.549 151 197 0.766 73 199 272 64 52 82 98 220
## 328 0.324 274 616 0.445 0.456 143 213 0.671 66 281 347 183 74 56 173 209
## 329 0.372 60 104 0.577 0.568 21 29 0.724 19 47 66 28 9 1 7 32
## 330 0.346 70 136 0.515 0.517 41 50 0.820 25 121 146 68 23 13 22 67
## 331 0.355 130 240 0.542 0.537 62 79 0.785 44 168 212 96 32 14 29 99
## 332 0.369 267 576 0.464 0.504 204 236 0.864 45 171 216 344 55 9 148 208
## 333 0.339 447 768 0.582 0.560 278 418 0.665 57 408 465 454 72 33 197 94
## 334 NA 10 16 0.625 0.625 7 8 0.875 6 15 21 3 3 3 1 8
## 335 1.000 0 0 NA 1.500 0 0 NA 0 1 1 1 0 0 0 0
## 336 0.357 20 47 0.426 0.485 15 18 0.833 6 30 36 21 0 2 9 10
## 337 0.379 20 47 0.426 0.505 15 18 0.833 6 31 37 22 0 2 9 10
## 338 0.367 94 167 0.563 0.556 64 80 0.800 72 216 288 96 27 18 43 137
## 339 0.500 3 14 0.214 0.281 4 8 0.500 4 15 19 1 1 3 0 7
## 340 0.300 67 117 0.573 0.541 31 41 0.756 47 100 147 60 16 13 45 99
## 341 0.000 1 1 1.000 0.500 0 0 NA 0 0 0 0 0 0 0 1
## 342 0.500 5 10 0.500 0.594 2 2 1.000 2 6 8 0 2 0 2 3
## 343 0.429 6 11 0.545 0.583 2 2 1.000 2 6 8 0 2 0 2 4
## 344 0.336 114 230 0.496 0.499 50 70 0.714 22 154 176 135 35 27 74 114
## 345 0.324 27 57 0.474 0.478 9 13 0.692 9 33 42 28 12 1 26 22
## 346 0.282 82 168 0.488 0.454 41 51 0.804 25 150 175 60 48 13 55 92
## 347 0.288 109 225 0.484 0.459 50 64 0.781 34 183 217 88 60 14 81 114
## 348 0.321 28 69 0.406 0.440 34 39 0.872 15 37 52 54 14 6 14 25
## 349 0.353 99 197 0.503 0.516 61 88 0.693 19 102 121 112 40 21 63 72
## 350 0.346 127 266 0.477 0.498 95 127 0.748 34 139 173 166 54 27 77 97
## 351 0.231 4 14 0.286 0.325 7 10 0.700 2 16 18 7 2 5 6 18
## 352 0.380 16 38 0.421 0.506 6 9 0.667 10 44 54 16 12 7 12 45
## 353 0.329 20 52 0.385 0.449 13 19 0.684 12 60 72 23 14 12 18 63
## 354 0.307 533 936 0.569 0.545 289 352 0.821 228 637 865 580 108 55 248 228
## 355 NA 53 74 0.716 0.716 24 37 0.649 31 44 75 28 12 25 16 63
## 356 0.308 132 233 0.567 0.537 74 122 0.607 96 144 240 37 46 42 43 123
## 357 0.357 16 34 0.471 0.500 19 27 0.704 11 23 34 7 9 2 8 27
## 358 0.200 10 23 0.435 0.394 1 2 0.500 16 33 49 13 7 5 5 10
## 359 0.000 1 2 0.500 0.250 0 1 0.000 0 4 4 0 0 0 1 1
## 360 0.317 145 320 0.453 0.460 58 69 0.841 23 111 134 327 81 5 47 78
## 361 NA 78 123 0.634 0.634 51 66 0.773 64 152 216 57 9 20 42 42
## 362 NA 208 323 0.644 0.644 135 198 0.682 161 525 686 99 33 53 111 125
## 363 NA 286 446 0.641 0.641 186 264 0.705 225 677 902 156 42 73 153 167
## 364 0.322 171 377 0.454 0.463 30 43 0.698 39 240 279 321 94 22 80 131
## 365 0.360 88 159 0.553 0.547 79 107 0.738 39 124 163 63 12 12 41 68
## 366 0.250 121 203 0.596 0.584 50 68 0.735 86 112 198 32 14 9 39 61
## 367 0.318 244 446 0.547 0.544 105 129 0.814 171 290 461 84 18 17 79 106
## 368 0.294 365 649 0.562 0.556 155 197 0.787 257 402 659 116 32 26 118 167
## 369 0.394 122 251 0.486 0.540 51 61 0.836 12 171 183 114 26 10 57 92
## 370 0.340 142 285 0.498 0.500 95 123 0.772 88 158 246 61 32 39 43 156
## 371 NA 0 0 NA NA 0 0 NA 0 1 1 0 0 0 0 0
## 372 0.353 98 168 0.583 0.553 58 74 0.784 90 239 329 70 36 78 54 143
## 373 0.156 6 15 0.400 0.287 9 11 0.818 1 8 9 9 2 0 5 14
## 374 0.371 52 116 0.448 0.498 18 23 0.783 9 41 50 62 19 2 25 48
## 375 0.318 58 131 0.443 0.460 27 34 0.794 10 49 59 71 21 2 30 62
## 376 0.343 213 550 0.387 0.438 162 226 0.717 61 274 335 82 43 24 114 175
## 377 0.326 51 101 0.505 0.496 36 44 0.818 16 91 107 52 29 2 25 62
## 378 0.363 37 90 0.411 0.502 38 46 0.826 28 107 135 54 27 42 25 41
## 379 0.463 10 22 0.455 0.625 13 16 0.813 0 29 29 17 3 2 17 22
## 380 0.384 53 113 0.469 0.547 47 57 0.825 9 124 133 64 22 10 42 84
## 381 0.397 63 135 0.467 0.559 60 73 0.822 9 153 162 81 25 12 59 106
## 382 NA 73 153 0.477 0.477 10 24 0.417 52 125 177 36 15 18 27 68
## 383 0.315 144 265 0.543 0.514 72 92 0.783 56 190 246 52 41 25 77 146
## 384 0.303 368 665 0.553 0.515 188 250 0.752 60 322 382 178 41 26 133 170
## 385 1.000 11 17 0.647 0.737 3 6 0.500 5 14 19 5 3 3 4 8
## 386 0.364 9 19 0.474 0.500 6 11 0.545 4 20 24 6 2 3 7 21
## 387 0.462 20 36 0.556 0.592 9 17 0.529 9 34 43 11 5 6 11 29
## 388 0.348 316 649 0.487 0.499 231 260 0.888 65 369 434 172 88 32 80 140
## 389 0.374 410 814 0.504 0.520 312 375 0.832 40 254 294 283 60 26 215 140
## 390 0.326 157 243 0.646 0.579 50 71 0.704 56 161 217 53 31 30 46 116
## 391 0.258 91 152 0.599 0.563 19 31 0.613 43 82 125 24 9 19 12 35
## 392 0.313 16 31 0.516 0.500 9 14 0.643 6 21 27 16 8 2 5 13
## 393 0.282 21 43 0.488 0.457 5 7 0.714 3 24 27 21 13 1 9 19
## 394 0.291 37 74 0.500 0.473 14 21 0.667 9 45 54 37 21 3 14 32
## 395 0.397 29 59 0.492 0.547 19 22 0.864 8 56 64 13 13 0 11 28
## 396 0.400 36 82 0.439 0.448 8 11 0.727 4 23 27 30 11 1 10 14
## 397 0.363 246 444 0.554 0.551 140 216 0.648 158 266 424 86 27 69 97 200
## 398 0.371 448 827 0.542 0.546 364 426 0.854 78 361 439 199 106 24 121 87
## 399 0.450 82 131 0.626 0.649 43 51 0.843 49 184 233 75 13 9 43 105
## 400 0.091 65 102 0.637 0.588 23 31 0.742 27 70 97 14 12 4 23 60
## 401 0.312 159 329 0.483 0.478 85 123 0.691 35 116 151 156 42 14 69 77
## 402 0.369 444 890 0.499 0.522 468 513 0.912 68 303 371 551 88 34 212 148
## 403 0.200 47 100 0.470 0.410 34 42 0.810 6 54 60 50 9 6 26 48
## 404 0.333 136 254 0.535 0.523 142 168 0.845 16 103 119 181 38 7 98 96
## 405 0.294 183 354 0.517 0.491 176 210 0.838 22 157 179 231 47 13 124 144
## 406 0.000 109 208 0.524 0.519 40 51 0.784 42 75 117 114 31 27 38 74
## 407 0.000 0 0 NA 0.000 0 0 NA 0 0 0 0 1 0 1 0
## 408 0.100 216 337 0.641 0.627 65 105 0.619 194 223 417 123 46 53 51 211
## 409 0.365 168 274 0.613 0.571 112 133 0.842 33 363 396 98 51 179 82 189
## 410 0.226 297 504 0.589 0.575 89 123 0.724 140 146 286 89 11 78 96 124
## 411 0.361 56 136 0.412 0.479 103 114 0.904 33 206 239 48 6 5 42 54
## 412 0.347 147 286 0.514 0.518 161 194 0.830 41 271 312 564 91 31 182 166
## 413 0.500 4 10 0.400 0.556 9 11 0.818 1 8 9 6 0 0 2 5
## 414 0.000 0 0 NA 0.000 2 2 1.000 0 3 3 1 0 0 0 1
## 415 0.227 8 21 0.381 0.360 4 6 0.667 4 14 18 4 4 1 5 14
## 416 0.330 38 81 0.469 0.483 27 35 0.771 7 72 79 22 15 7 16 59
## 417 0.310 46 102 0.451 0.459 31 41 0.756 11 86 97 26 19 8 21 73
## 418 0.400 5 8 0.625 0.611 1 3 0.333 7 11 18 6 2 0 4 10
## 419 0.255 156 295 0.529 0.470 81 116 0.698 44 202 246 87 30 23 68 93
## 420 1.000 3 5 0.600 0.750 1 1 1.000 0 0 0 3 1 0 0 2
## 421 0.000 2 12 0.167 0.143 5 9 0.556 0 2 2 1 2 0 4 3
## 422 0.359 115 261 0.441 0.473 53 75 0.707 18 84 102 182 45 4 62 81
## 423 0.354 117 273 0.429 0.462 58 84 0.690 18 86 104 183 47 4 66 84
## 424 0.455 5 16 0.313 0.463 4 7 0.571 2 10 12 7 1 0 6 8
## 425 0.000 3 5 0.600 0.333 0 0 NA 0 3 3 2 0 0 0 0
## 426 0.188 44 88 0.500 0.466 42 61 0.689 48 80 128 25 25 16 21 84
## 427 0.307 27 59 0.458 0.459 36 47 0.766 24 82 106 27 11 33 24 50
## 428 0.333 33 56 0.589 0.537 20 37 0.541 17 79 96 18 10 18 9 55
## 429 0.320 60 115 0.522 0.498 56 84 0.667 41 161 202 45 21 51 33 105
## 430 0.500 71 112 0.634 0.642 26 36 0.722 32 81 113 32 5 10 22 33
## 431 0.000 85 138 0.616 0.607 72 95 0.758 55 97 152 22 11 17 37 57
## 432 0.400 156 250 0.624 0.623 98 131 0.748 87 178 265 54 16 27 59 90
## 433 0.361 222 463 0.479 0.506 170 195 0.872 74 396 470 75 37 33 85 122
## 434 0.351 23 47 0.489 0.510 9 11 0.818 11 62 73 18 3 8 11 51
## 435 0.219 57 105 0.543 0.462 39 57 0.684 6 37 43 84 16 4 36 34
## 436 0.000 1 3 0.333 0.250 0 0 NA 1 2 3 0 1 0 0 0
## 437 0.200 2 9 0.222 0.263 4 5 0.800 1 2 3 5 1 1 2 2
## 438 0.369 33 80 0.413 0.500 41 48 0.854 11 54 65 55 20 4 31 56
## 439 0.380 94 206 0.456 0.520 87 110 0.791 20 82 102 100 33 12 58 102
## 440 0.372 129 295 0.437 0.507 132 163 0.810 32 138 170 160 54 17 91 160
## 441 0.333 6 12 0.500 0.500 2 5 0.400 2 5 7 2 1 1 2 8
## 442 0.000 2 2 1.000 0.667 0 1 0.000 0 1 1 0 0 0 0 2
## 443 0.250 1 5 0.200 0.278 0 0 NA 0 3 3 2 2 0 3 1
## 444 0.333 16 30 0.533 0.519 13 15 0.867 7 38 45 27 21 2 14 37
## 445 0.321 17 35 0.486 0.484 13 15 0.867 7 41 48 29 23 2 17 38
## 446 0.375 404 798 0.506 0.527 159 192 0.828 62 220 282 207 55 28 106 172
## 447 0.333 206 377 0.546 0.542 29 37 0.784 28 146 174 258 79 17 91 105
## 448 0.408 123 216 0.569 0.590 66 79 0.835 17 92 109 67 18 8 42 104
## 449 0.083 399 629 0.634 0.625 96 152 0.632 195 371 566 52 47 148 108 208
## 450 0.351 107 236 0.453 0.489 52 72 0.722 60 178 238 112 36 12 64 115
## 451 0.356 92 157 0.586 0.564 27 48 0.563 81 166 247 31 18 15 30 134
## 452 0.415 8 23 0.348 0.523 8 12 0.667 3 14 17 4 6 3 5 22
## 453 0.286 51 95 0.537 0.508 28 35 0.800 6 34 40 30 13 7 15 26
## 454 0.444 13 21 0.619 0.641 1 1 1.000 1 11 12 8 1 1 2 5
## 455 0.324 44 78 0.564 0.540 20 32 0.625 36 95 131 35 10 26 21 55
## 456 0.305 71 161 0.441 0.447 21 28 0.750 25 109 134 159 68 23 75 113
## 457 0.000 19 56 0.339 0.328 13 17 0.765 9 27 36 13 6 2 15 14
## 458 0.378 327 674 0.485 0.519 216 258 0.837 50 411 461 331 80 7 174 172
## 459 0.364 18 39 0.462 0.514 13 14 0.929 1 26 27 14 8 5 9 17
## 460 0.314 27 69 0.391 0.444 35 44 0.795 12 56 68 22 18 10 21 62
## 461 0.330 45 108 0.417 0.468 48 58 0.828 13 82 95 36 26 15 30 79
## 462 0.365 56 120 0.467 0.528 56 71 0.789 14 114 128 146 40 23 59 165
## 463 0.476 1 5 0.200 0.615 3 4 0.750 1 4 5 1 1 1 1 5
## 464 0.394 123 259 0.475 0.545 88 103 0.854 24 158 182 245 49 10 93 129
## 465 0.365 264 506 0.522 0.528 181 249 0.727 153 352 505 141 83 54 95 183
## 466 0.318 20 43 0.465 0.471 5 7 0.714 9 26 35 18 8 8 6 29
## 467 0.356 25 48 0.521 0.530 20 23 0.870 14 61 75 20 10 9 11 21
## 468 0.368 97 176 0.551 0.552 85 101 0.842 46 218 264 35 21 25 37 86
## 469 0.365 122 224 0.545 0.546 105 124 0.847 60 279 339 55 31 34 48 107
## 470 0.362 473 1011 0.468 0.493 319 396 0.806 59 257 316 322 106 31 218 208
## 471 0.182 4 9 0.444 0.350 2 2 1.000 1 5 6 15 1 1 8 10
## 472 0.330 118 256 0.461 0.480 90 102 0.882 16 121 137 117 37 19 86 106
## 473 NA 3 5 0.600 0.600 0 0 NA 3 0 3 1 0 0 0 0
## 474 1.000 14 22 0.636 0.674 10 11 0.909 4 9 13 7 1 0 1 5
## 475 0.000 74 157 0.471 0.460 35 61 0.574 60 96 156 16 13 8 31 61
## 476 0.200 91 184 0.495 0.489 45 72 0.625 67 105 172 24 14 8 32 66
## 477 0.432 180 356 0.506 0.553 45 59 0.763 35 92 127 102 40 8 59 112
## 478 NA 0 0 NA NA 0 0 NA 0 3 3 0 0 0 0 1
## 479 1.000 2 6 0.333 0.500 0 0 NA 4 16 20 4 1 1 5 9
## 480 1.000 2 6 0.333 0.500 0 0 NA 4 13 17 4 1 1 5 8
## 481 0.333 3 7 0.429 0.450 1 2 0.500 0 5 5 4 2 0 1 1
## 482 0.375 231 455 0.508 0.533 146 173 0.844 76 382 458 109 43 25 92 181
## 483 0.339 41 97 0.423 0.455 14 19 0.737 20 71 91 19 11 2 7 58
## 484 0.333 95 184 0.516 0.509 57 73 0.781 41 133 174 60 25 20 47 117
## 485 0.335 136 281 0.484 0.492 71 92 0.772 61 204 265 79 36 22 54 175
## 486 0.414 252 475 0.531 0.560 65 81 0.802 35 159 194 297 73 4 52 102
## 487 NA 3 6 0.500 0.500 0 2 0.000 2 1 3 1 0 1 3 6
## 488 0.000 39 70 0.557 0.534 24 40 0.600 18 33 51 11 5 3 16 27
## 489 0.329 261 530 0.492 0.493 144 186 0.774 33 163 196 228 43 19 140 103
## 490 0.367 361 759 0.476 0.502 189 223 0.848 65 252 317 363 67 27 158 153
## 491 0.100 8 12 0.667 0.432 0 2 0.000 1 4 5 2 2 0 4 1
## 492 0.368 15 26 0.577 0.560 7 8 0.875 6 38 44 14 4 11 5 18
## 493 0.342 41 79 0.519 0.514 63 77 0.818 51 149 200 62 18 27 43 112
## 494 0.348 56 105 0.533 0.525 70 85 0.824 57 187 244 76 22 38 48 130
## 495 0.500 0 4 0.000 0.375 0 0 NA 1 1 2 4 1 0 1 0
## 496 0.318 17 47 0.362 0.436 12 20 0.600 8 26 34 33 13 1 20 25
## 497 0.326 17 51 0.333 0.432 12 20 0.600 9 27 36 37 14 1 21 25
## 498 0.320 59 115 0.513 0.498 27 36 0.750 14 102 116 20 20 12 26 68
## 499 0.337 216 381 0.567 0.554 96 134 0.716 168 384 552 214 100 40 97 192
## 500 0.333 93 207 0.449 0.476 115 138 0.833 18 82 100 143 41 16 66 67
## 501 0.333 54 101 0.535 0.522 28 33 0.848 6 56 62 93 14 4 35 49
## 502 0.410 43 76 0.566 0.594 20 24 0.833 11 76 87 35 10 6 23 57
## 503 0.000 110 212 0.519 0.516 78 109 0.716 58 180 238 89 20 31 50 96
## 504 NA 162 276 0.587 0.587 54 79 0.684 127 198 325 45 66 96 48 166
## 505 0.312 71 171 0.415 0.444 39 50 0.780 5 153 158 35 9 18 18 76
## 506 0.287 62 167 0.371 0.395 23 30 0.767 12 75 87 121 30 14 56 104
## 507 0.250 0 1 0.000 0.346 0 0 NA 0 1 1 2 0 0 0 6
## 508 0.385 4 8 0.500 0.548 4 4 1.000 0 4 4 5 1 0 1 4
## 509 0.320 4 9 0.444 0.471 4 4 1.000 0 5 5 7 1 0 1 10
## 510 0.103 417 797 0.523 0.510 282 365 0.773 243 505 748 233 71 103 168 250
## 511 0.320 102 187 0.545 0.527 58 85 0.682 41 122 163 54 36 17 29 106
## 512 0.386 95 167 0.569 0.574 32 42 0.762 22 263 285 124 54 24 70 172
## 513 0.083 68 124 0.548 0.511 17 21 0.810 29 90 119 56 9 25 31 68
## 514 0.315 39 69 0.565 0.513 24 39 0.615 24 62 86 23 10 4 19 43
## 515 0.200 211 357 0.591 0.587 59 89 0.663 82 196 278 40 15 40 52 96
## 516 0.295 75 158 0.475 0.460 37 47 0.787 12 86 98 127 32 7 69 109
## 517 0.279 136 293 0.464 0.445 118 162 0.728 41 177 218 91 88 33 63 166
## 518 0.343 175 372 0.470 0.486 103 141 0.730 21 181 202 186 60 11 82 72
## 519 0.354 148 245 0.604 0.563 152 185 0.822 72 303 375 140 53 37 114 183
## 520 0.348 230 470 0.489 0.504 141 181 0.779 45 312 357 195 60 11 114 195
## 521 0.311 91 173 0.526 0.500 68 85 0.800 24 105 129 20 27 20 30 71
## 522 0.325 176 331 0.532 0.515 121 159 0.761 47 149 196 64 57 39 73 110
## 523 0.320 267 504 0.530 0.510 189 244 0.775 71 254 325 84 84 59 103 181
## 524 0.000 85 189 0.450 0.440 97 124 0.782 99 166 265 91 31 17 57 151
## 525 0.296 125 204 0.613 0.565 52 76 0.684 38 142 180 68 23 16 67 58
## 526 0.325 183 350 0.523 0.514 79 108 0.731 41 200 241 84 23 14 84 87
## 527 0.313 308 554 0.556 0.533 131 184 0.712 79 342 421 152 46 30 151 145
## 528 0.255 200 412 0.485 0.474 91 124 0.734 14 69 83 207 21 7 75 53
## 529 0.309 39 88 0.443 0.453 22 25 0.880 4 66 70 43 19 5 32 45
## 530 0.336 36 82 0.439 0.479 19 30 0.633 42 105 147 31 16 13 22 46
## 531 0.000 2 5 0.400 0.286 1 2 0.500 2 4 6 3 2 0 0 5
## 532 0.358 175 365 0.479 0.508 175 203 0.862 36 229 265 473 114 18 152 146
## 533 0.360 18 30 0.600 0.573 11 16 0.688 3 16 19 23 8 3 11 15
## 534 0.271 53 109 0.486 0.458 22 25 0.880 10 43 53 83 20 6 34 49
## 535 0.298 71 139 0.511 0.487 33 41 0.805 13 59 72 106 28 9 45 64
## 536 0.314 146 307 0.476 0.475 55 74 0.743 49 171 220 320 44 17 112 81
## 537 0.500 4 6 0.667 0.688 0 0 NA 1 1 2 4 3 1 1 2
## 538 0.261 13 27 0.481 0.425 19 22 0.864 4 32 36 21 6 0 18 15
## 539 0.200 260 432 0.602 0.595 111 198 0.561 165 359 524 243 66 76 126 252
## 540 NA 32 48 0.667 0.667 16 30 0.533 16 23 39 17 6 4 10 14
## 541 0.333 23 40 0.575 0.552 34 42 0.810 8 38 46 24 11 1 13 24
## 542 0.488 58 121 0.479 0.580 29 32 0.906 14 69 83 40 18 9 25 29
## 543 0.369 137 266 0.515 0.531 49 64 0.766 40 191 231 80 64 22 40 79
## 544 0.406 195 387 0.504 0.546 78 96 0.813 54 260 314 120 82 31 65 108
## 545 0.375 95 199 0.477 0.500 39 50 0.780 46 115 161 29 11 8 29 61
## 546 0.403 109 238 0.458 0.507 38 47 0.809 63 179 242 43 24 12 45 84
## 547 0.393 204 437 0.467 0.504 77 97 0.794 109 294 403 72 35 20 74 145
## 548 0.307 251 359 0.699 0.637 196 254 0.772 140 271 411 112 44 50 67 201
## 549 0.400 125 230 0.543 0.568 62 75 0.827 16 123 139 91 39 13 65 96
## 550 0.391 31 58 0.534 0.549 18 29 0.621 29 47 76 17 4 10 13 47
## 551 NA 187 290 0.645 0.645 49 92 0.533 178 232 410 93 29 68 48 124
## 552 NA 1 1 1.000 1.000 0 0 NA 0 0 0 0 0 0 0 0
## 553 0.200 113 197 0.574 0.554 49 69 0.710 70 136 206 54 17 14 35 90
## 554 0.400 45 102 0.441 0.525 43 62 0.694 10 46 56 97 25 3 43 91
## 555 0.344 504 894 0.564 0.555 356 487 0.731 162 472 634 229 52 45 208 246
## 556 0.397 212 422 0.502 0.557 228 255 0.894 20 166 186 206 32 17 101 129
## 557 0.500 3 8 0.375 0.500 0 0 NA 2 4 6 3 1 0 1 3
## 558 0.412 12 27 0.444 0.558 8 9 0.889 4 27 31 13 6 2 5 26
## 559 0.357 259 566 0.458 0.492 199 231 0.861 54 209 263 298 79 34 113 200
## 560 0.320 1 4 0.250 0.448 4 5 0.800 2 11 13 0 1 0 8 13
## 561 0.311 43 88 0.489 0.477 25 46 0.543 10 61 71 58 18 10 36 72
## 562 0.321 85 157 0.541 0.507 25 49 0.510 15 76 91 109 29 13 32 135
## 563 0.318 128 245 0.522 0.497 50 95 0.526 25 137 162 167 47 23 68 207
## 564 0.000 19 30 0.633 0.594 9 14 0.643 6 14 20 6 4 6 2 11
## 565 0.286 8 11 0.727 0.500 4 6 0.667 2 17 19 5 5 0 4 11
## 566 0.290 56 114 0.491 0.472 32 40 0.800 17 54 71 21 14 8 18 45
## 567 0.316 26 53 0.491 0.482 6 9 0.667 3 38 41 19 11 3 13 46
## 568 NA 202 291 0.694 0.694 81 135 0.600 177 246 423 37 52 161 35 217
## 569 0.359 124 290 0.428 0.464 23 36 0.639 34 209 243 367 57 7 127 100
## 570 0.370 309 607 0.509 0.518 137 160 0.856 33 107 140 220 31 12 82 57
## 571 0.383 223 461 0.484 0.534 126 144 0.875 27 253 280 135 72 29 90 119
## 572 0.353 139 329 0.422 0.477 73 93 0.785 32 275 307 231 68 21 68 101
## 573 0.311 216 476 0.454 0.458 195 228 0.855 33 210 243 416 91 10 180 180
## 574 0.369 425 882 0.482 0.512 160 205 0.780 53 262 315 563 100 20 253 141
## 575 0.529 404 683 0.592 0.596 208 291 0.715 186 504 690 212 48 30 160 239
## 576 0.379 17 31 0.548 0.558 4 6 0.667 3 13 16 10 8 3 12 19
## 577 0.357 24 40 0.600 0.583 17 21 0.810 5 27 32 4 4 3 4 8
## 578 0.395 193 368 0.524 0.545 131 160 0.819 82 197 279 399 82 13 120 172
## 579 0.341 333 740 0.450 0.470 186 227 0.819 38 246 284 323 65 12 172 189
## 580 0.412 27 71 0.380 0.529 10 15 0.667 19 83 102 22 9 5 17 68
## 581 0.391 40 97 0.412 0.513 12 18 0.667 24 150 174 44 17 8 27 88
## 582 0.401 67 168 0.399 0.520 22 33 0.667 43 233 276 66 26 13 44 156
## 583 0.436 37 71 0.521 0.591 14 22 0.636 8 115 123 27 43 5 25 41
## 584 0.317 45 98 0.459 0.466 22 29 0.759 16 28 44 36 10 6 23 48
## 585 0.315 96 211 0.455 0.461 45 63 0.714 21 115 136 73 23 7 56 83
## 586 0.316 141 309 0.456 0.463 67 92 0.728 37 143 180 109 33 13 79 131
## 587 0.402 400 910 0.440 0.480 214 255 0.839 57 179 236 243 44 6 185 186
## 588 0.450 19 59 0.322 0.576 31 39 0.795 7 49 56 58 13 2 19 49
## 589 0.404 54 102 0.529 0.584 44 54 0.815 14 64 78 59 24 8 26 106
## 590 0.422 73 161 0.453 0.581 75 93 0.806 21 113 134 117 37 10 45 155
## 591 0.296 13 27 0.481 0.454 2 4 0.500 8 46 54 21 12 4 12 35
## 592 0.366 59 146 0.404 0.489 34 41 0.829 19 110 129 91 47 20 38 92
## 593 0.348 72 173 0.416 0.481 36 45 0.800 27 156 183 112 59 24 50 127
## 594 0.369 440 731 0.602 0.591 237 302 0.785 124 425 549 248 73 52 154 241
## 595 1.000 0 0 NA 1.500 0 0 NA 0 0 0 0 0 0 0 0
## 596 0.000 540 954 0.566 0.563 257 428 0.600 172 525 697 610 112 61 274 209
## 597 0.429 20 43 0.465 0.523 16 25 0.640 4 22 26 33 11 1 12 21
## 598 0.229 85 203 0.419 0.397 56 72 0.778 23 77 100 95 18 14 56 68
## 599 0.269 105 246 0.427 0.420 72 97 0.742 27 99 126 128 29 15 68 89
## 600 NA 0 0 NA NA 0 0 NA 0 0 0 0 0 0 0 0
## 601 0.345 18 34 0.529 0.524 9 16 0.563 3 10 13 13 1 0 11 9
## 602 0.364 113 221 0.511 0.533 104 129 0.806 57 177 234 321 143 28 123 201
## 603 0.289 97 210 0.462 0.454 42 74 0.568 14 44 58 114 27 9 54 47
## 604 0.344 114 232 0.491 0.500 57 82 0.695 18 79 97 138 40 11 100 82
## 605 0.322 211 442 0.477 0.479 99 156 0.635 32 123 155 252 67 20 154 129
## 606 0.326 161 354 0.455 0.464 47 62 0.758 23 122 145 203 28 11 61 109
## 607 0.308 15 40 0.375 0.418 8 10 0.800 0 18 18 21 11 3 11 19
## 608 0.286 0 2 0.000 0.333 2 2 1.000 2 2 4 1 0 0 1 3
## 609 0.333 1 4 0.250 0.423 2 2 1.000 3 8 11 1 2 2 5 6
## 610 0.400 11 27 0.407 0.459 10 12 0.833 11 26 37 12 1 5 7 21
## 611 0.346 12 33 0.364 0.432 14 16 0.875 16 36 52 14 3 7 13 30
## 612 0.375 8 18 0.444 0.500 6 8 0.750 3 10 13 10 2 2 6 8
## 613 0.397 82 157 0.522 0.564 37 42 0.881 29 128 157 68 26 18 23 90
## 614 NA 0 0 NA NA 0 0 NA 0 0 0 0 0 0 0 0
## 615 0.000 25 44 0.568 0.532 4 12 0.333 15 33 48 5 9 8 9 23
## 616 0.000 25 44 0.568 0.532 4 12 0.333 15 33 48 5 9 8 9 23
## 617 0.344 54 116 0.466 0.492 32 45 0.711 72 122 194 47 26 25 31 67
## 618 0.429 13 46 0.283 0.491 25 28 0.893 8 39 47 19 7 3 11 19
## 619 0.344 53 104 0.510 0.513 32 36 0.889 10 70 80 62 14 4 40 31
## 620 0.372 66 150 0.440 0.506 57 64 0.891 18 109 127 81 21 7 51 50
## 621 NA 1 2 0.500 0.500 0 0 NA 0 0 0 0 1 0 1 0
## 622 0.371 111 235 0.472 0.510 50 73 0.685 32 183 215 140 41 7 86 111
## 623 0.259 15 37 0.405 0.398 15 24 0.625 9 15 24 10 12 5 10 26
## 624 0.000 4 7 0.571 0.444 0 2 0.000 4 8 12 4 2 1 2 6
## 625 0.200 13 39 0.333 0.330 6 7 0.857 13 39 52 7 4 0 16 22
## 626 0.143 17 46 0.370 0.349 6 9 0.667 17 47 64 11 6 1 18 28
## 627 0.373 350 725 0.483 0.506 195 228 0.855 70 407 477 168 84 57 122 168
## 628 0.333 141 311 0.453 0.465 123 153 0.804 16 90 106 343 43 18 97 90
## 629 0.296 26 52 0.500 0.472 23 31 0.742 10 54 64 37 26 5 16 70
## 630 0.352 92 177 0.520 0.525 57 76 0.750 18 134 152 69 50 25 54 134
## 631 0.341 118 229 0.515 0.513 80 107 0.748 28 188 216 106 76 30 70 204
## 632 0.370 7 13 0.538 0.550 4 7 0.571 3 13 16 32 3 1 21 27
## 633 0.235 8 22 0.364 0.359 3 6 0.500 1 5 6 12 3 2 10 16
## 634 NA 0 1 0.000 0.000 1 2 0.500 1 0 1 1 0 0 0 0
## 635 NA 4 6 0.667 0.667 1 2 0.500 2 4 6 1 3 0 2 4
## 636 NA 4 7 0.571 0.571 2 4 0.500 3 4 7 2 3 0 2 4
## 637 0.388 120 199 0.603 0.598 56 76 0.737 87 138 225 68 21 42 33 161
## 638 0.279 22 56 0.393 0.404 17 27 0.630 5 8 13 23 5 1 18 17
## 639 0.286 12 34 0.353 0.391 7 11 0.636 4 16 20 8 7 5 4 22
## 640 0.278 56 118 0.475 0.452 27 36 0.750 21 96 117 27 17 7 24 83
## 641 0.402 414 803 0.516 0.553 129 158 0.816 37 262 299 186 84 47 115 157
## 642 NA 201 380 0.529 0.529 68 106 0.642 173 265 438 86 28 16 59 89
## 643 0.200 14 34 0.412 0.378 25 34 0.735 5 39 44 18 14 7 20 41
## 644 0.377 18 44 0.409 0.539 47 60 0.783 15 162 177 46 17 21 36 91
## 645 0.400 539 959 0.562 0.572 376 450 0.836 263 691 954 259 67 125 240 292
## 646 0.238 11 29 0.379 0.370 3 7 0.429 1 10 11 5 1 2 4 4
## 647 0.394 180 386 0.466 0.498 179 223 0.803 31 166 197 119 28 14 116 117
## 648 0.377 61 136 0.449 0.535 41 59 0.695 121 358 479 96 132 39 63 252
## 649 0.212 193 391 0.494 0.473 75 106 0.708 37 291 328 283 33 18 114 110
## 650 0.388 304 584 0.521 0.536 148 201 0.736 101 430 531 115 60 199 100 195
## 651 NA 50 72 0.694 0.694 19 30 0.633 27 63 90 28 10 31 13 36
## 652 NA 0 0 NA NA 0 0 NA 0 0 0 0 0 0 0 0
## 653 0.278 147 261 0.563 0.554 70 91 0.769 52 151 203 41 6 30 51 64
## 654 0.300 140 229 0.611 0.593 77 94 0.819 54 162 216 29 13 23 39 82
## 655 0.292 287 490 0.586 0.572 147 185 0.795 106 313 419 70 19 53 90 146
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## 674 0.338 212 401 0.529 0.523 95 123 0.772 35 212 247 263 67 47 97 145
## 675 0.000 0 0 NA 0.000 0 0 NA 1 1 2 0 0 0 0 0
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## 708 NA 183 331 0.553 0.553 93 132 0.705 108 212 320 53 13 22 61 113
## PTS player_id salary
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## 441 20 NA NA
## 442 4 356 47370
## 443 5 357 964104
## 444 69 357 964104
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## 614 0 NA NA
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## 708 459 574 1952760sum(is.na(pms))## [1] 161which(is.na(pms), arr.ind = TRUE)## row col
## [1,] 303 10
## [2,] 371 10
## [3,] 478 10
## [4,] 600 10
## [5,] 614 10
## [6,] 652 10
## [7,] 19 13
## [8,] 21 13
## [9,] 59 13
## [10,] 66 13
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## [161,] 682 31naniar::vis_miss(pms)
pms[is.na(pms)] = 0sum(is.na(pms))## [1] 05. Player recommendations
After developing the winning percentage model based on team statistic, the model can next be applied on team player selection by introducing team player statistic. The two provided data sets of team player statistics and team player salaries are first combined. No missing values are found with the chosen data (player_id,Age, TM,GS,POS,PTS,FGS,FTA,TOV,TRB,salary) for interpretation. By considering some players with limited game starts who may give a very high true shooting percentage, only player with game start >41games (half-season) is considered in this model.
filtered player data
pmsf <- subset(pms, select = c("player_name", "player_id","Age" ,"Tm", "GS", "Pos", "PTS","FGA","FTA", "TOV","TRB", "salary"))
## game start more than 41 games will be considered (Half of the regular season)
pmsf <- pmsf %>% filter( GS >= 41)
## calculating true shooting%
## TS. = Points/[2*(Field Goals Attempted + 0.44 * Free Throws Attempted)]
pmsf <- mutate(pmsf, TS. = PTS/(2*(FGA + 0.44* FTA)))
pmsf <- mutate(pmsf, win_score = -369 + TS. * 426.9 + TOV * -0.04355 + TRB * 0.03569 + Age * 3.73282)duplicated(pmsf)## [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [49] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [61] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [73] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [85] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [97] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [109] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [121] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [133] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [145] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSEpmsf <- pmsf%>% distinct(player_name, .keep_all = TRUE)pmsf %>% select(player_name, Pos, salary, win_score) %>%
arrange(desc(win_score)) %>% top_n(10)## Selecting by win_score## player_name Pos salary win_score
## 1 Rudy Gobert C 23491573 50.58856
## 2 DeAndre Jordan C 22897200 49.40593
## 3 JaVale McGee C 2393887 32.69070
## 4 Taj Gibson PF 14000000 28.74703
## 5 Clint Capela C 15793104 27.54803
## 6 Danny Green SG 10000000 24.63439
## 7 Danilo Gallinari SF 21587579 23.92374
## 8 Stephen Curry PG 37457154 21.61442
## 9 Al Horford C 28928710 20.51479
## 10 Kevin Durant SF 30000000 20.38839A table with volumes of player_name, POS, Salary and WIN_score is shown for clearing presentation and comparison among players. The original goal of the analysis is to select the best five starting players that my team can afford, which proving that they are worth it based on the provided team and player statistic. A graph of player salary against win score is then plotted for visualisation comparison. Hence, players of high win score and low salary (left top quarter of the graph) is desirable. The same plots are applied to each of the position (POS) point guard, shooting guard, small forward, power forward and centre to evaluate player selection.
player_labels <- if_else(pmsf$win_score >= 0, paste(pmsf$player_id), "")
pmsf %>% ggplot(aes(salary, win_score, color = Pos )) +
geom_point()+
geom_text(aes(label= player_labels), nudge_y = 6, nudge_x = 0.25)
Top 10 point guard
dat_pg <- filter(pmsf, Pos == "PG")
dat_pg <- subset(dat_pg, select = c("player_name", "player_id" ,"Pos", "salary", "win_score"))
dat_pg %>% arrange(desc(win_score)) %>% top_n(10)## Selecting by win_score## player_name player_id Pos salary win_score
## 1 Stephen Curry 132 PG 37457154 21.614424
## 2 DJ Augustin 28 PG 7250000 11.536498
## 3 James Harden 224 PG 30570000 3.949789
## 4 Chris Paul 428 PG 35654150 -4.030314
## 5 Darren Collison 117 PG 10000000 -5.263312
## 6 Kyle Lowry 337 PG 32700000 -6.573124
## 7 Patrick Beverley 52 PG 5027028 -7.345029
## 8 Mike Conley 119 PG 30521115 -7.483797
## 9 Eric Bledsoe 59 PG 15000000 -8.566858
## 10 Damian Lillard 328 PG 27977689 -9.607731Top 10 shooting guard
dat_sg <- filter(pmsf, Pos == "SG")
dat_sg <- subset(dat_sg, select = c("player_name", "player_id" ,"Pos", "salary", "win_score"))
dat_sg %>% arrange(desc(win_score)) %>% top_n(10)## Selecting by win_score## player_name player_id Pos salary win_score
## 1 Danny Green 215 SG 10000000 24.634387
## 2 JJ Redick 452 SG 12250000 17.225017
## 3 Joe Harris 229 SG 8333333 12.408815
## 4 Malcolm Brogdon 77 SG 1544951 -3.428661
## 5 Garrett Temple 509 SG 8000000 -11.419616
## 6 Buddy Hield 244 SG 3833760 -13.207772
## 7 Klay Thompson 517 SG 18988725 -15.127103
## 8 Bryn Forbes 181 SG 3125000 -20.541323
## 9 DeMar DeRozan 145 SG 27739975 -21.352242
## 10 Eric Gordon 207 SG 13500375 -21.360775Top 10 small forward
dat_sf <- filter(pmsf, Pos == "SF")
dat_sf <- subset(dat_sf, select = c("player_name", "player_id" ,"Pos", "salary", "win_score"))
dat_sf %>% arrange(desc(win_score)) %>% top_n(10)## Selecting by win_score## player_name player_id Pos salary win_score
## 1 Danilo Gallinari 191 SF 21587579 23.923737412
## 2 Kevin Durant 160 SF 30000000 20.388386014
## 3 LeBron James 278 SF 35654150 17.114822999
## 4 Bojan Bogdanovic 62 SF 10500000 7.160704877
## 5 Kawhi Leonard 324 SF 23114066 0.962871973
## 6 Nicolas Batum 39 SF 24000000 -0.002232873
## 7 Paul George 197 SF 30560700 -2.108804413
## 8 Trevor Ariza 25 SF 15000000 -10.985351850
## 9 Jimmy Butler 91 SF 19841627 -11.093456911
## 10 Wesley Matthews 354 SF 19360228 -11.222775168Top 10 power forward
dat_pf <- filter(pmsf, Pos == "PF")
dat_pf <- subset(dat_pf, select = c("player_name", "player_id" ,"Pos", "salary", "win_score"))
dat_pf %>% arrange(desc(win_score)) %>% top_n(10) ## Selecting by win_score## player_name player_id Pos salary win_score
## 1 Taj Gibson 198 PF 14000000 28.7470319
## 2 Jeff Green 217 PF 2393887 16.7420830
## 3 Giannis Antetokounmpo 20 PF 24157304 15.7646526
## 4 Paul Millsap 375 PF 29230769 11.4027009
## 5 Rudy Gay 196 PF 10087200 11.3392548
## 6 Nemanja Bjelica 57 PF 6500000 4.9385397
## 7 PJ Tucker 525 PF 7959537 2.2194325
## 8 Pascal Siakam 482 PF 1544951 1.6041736
## 9 Thaddeus Young 568 PF 13764045 -0.9554026
## 10 Joe Ingles 266 PF 12545455 -2.0834403Top 10 center
dat_c <- filter(pmsf, Pos == "C")
dat_c <- subset(dat_c, select = c("player_name", "player_id" ,"Pos", "salary", "win_score"))
dat_c %>% arrange(desc(win_score)) %>% top_n(10)## Selecting by win_score## player_name player_id Pos salary win_score
## 1 Rudy Gobert 203 C 23491573 50.588564
## 2 DeAndre Jordan 298 C 22897200 49.405932
## 3 JaVale McGee 361 C 2393887 32.690700
## 4 Clint Capela 96 C 15793104 27.548033
## 5 Al Horford 256 C 28928710 20.514790
## 6 LaMarcus Aldridge 10 C 22347015 20.171455
## 7 Derrick Favors 175 C 16900000 14.288852
## 8 Thomas Bryant 86 C 1378242 10.727755
## 9 Dewayne Dedmon 139 C 6300000 9.656709
## 10 Brook Lopez 335 C 3382000 8.568587Best five starting players
The following 5 players are selected:
1) PG- Point Guard - Stephen Curry
2) SG- Shooting Guard - Danny Green
3) SF- Small Forward - Danilo Gallinari
4) PF- Power Forward - Taj Gibson
5) C- Centre - Rudy Gobert
With total salaries of five starters is 107million, which is under our team next season player contract budget of $118 million.
dat_pg_start <- dat_pg %>% arrange(desc(win_score)) %>% top_n(10)%>% slice_max(1)
dat_sg_start <- dat_sg %>% arrange(desc(win_score)) %>% top_n(10)%>% slice_max(1)
dat_sf_start <- dat_sf %>% arrange(desc(win_score)) %>% top_n(10) %>% slice_max(1)
dat_pf_start <- dat_pf %>% arrange(desc(win_score)) %>% top_n(10)%>% slice_max(1)
dat_c_start <- dat_c %>% arrange(desc(win_score)) %>% top_n(10)%>% slice_max(1)dat_start_five <- bind_rows(dat_pg_start,dat_sg_start, dat_sf_start, dat_pf_start, dat_c_start)
tibble(dat_start_five)## # A tibble: 5 x 5
## player_name player_id Pos salary win_score
## <chr> <dbl> <chr> <dbl> <dbl>
## 1 Stephen Curry 132 PG 37457154 21.6
## 2 Danny Green 215 SG 10000000 24.6
## 3 Danilo Gallinari 191 SF 21587579 23.9
## 4 Taj Gibson 198 PF 14000000 28.7
## 5 Rudy Gobert 203 C 23491573 50.6total salaries of five starters
exp_salary <- sum(dat_start_five$salary)
print(exp_salary)## [1] 106536306##check the expecting lineup salary
exp_salary <- sum(dat_start_five$salary)
if(exp_salary < 118000000)
print("Within Buget")## [1] "Within Buget"